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AIR COMMAND AND STAFF COLLEGE

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Using an Intratheater Regional

Hub Heuristic in Iraq

An Exploratory Case Study

Robert L. Charlesworth

Major, USAF

Air Command and Staff College

Wright Flyer Paper No. 25

Air University Press

Maxwell Air Force Base, Alabama

May 2007
ii

Disclaimer

Opinions, conclusions, and recommendations expressed or implied within are solely 

those of the author and do not necessarily represent the views of Air University, the 

United States Air Force, the Department of Defense, or any other US government agency. 

Cleared for public release: distribution unlimited.

This Wright Flyer Paper and others in the series are 

available electronically at the Air University Research 

Web site http://research.maxwell.af.mil and the AU 

Press Web site http://aupress.maxwell.af.mil.
iii

Foreword

It is my great pleasure to present another of the Wright 

Flyer Papers series. In this series, Air Command and Staff 

College (ACSC) recognizes and publishes our best student 

research projects from the prior academic year. The ACSC 

research program encourages our students to move beyond 

the school’s core curriculum in their own professional development and in “advancing air and space power.” The 

series title reflects our desire to perpetuate the pioneering 

spirit embodied in earlier generations of Airmen. Projects 

selected for publication combine solid research, innovative 

thought, and lucid presentation in exploring war at the operational level. With this broad perspective, the Wright Flyer 

Papers engage an eclectic range of doctrinal, technological, 

organizational, and operational questions. Some of these 

studies provide new solutions to familiar problems. Others encourage us to leave the familiar behind in pursuing 

new possibilities. By making these research studies available in the Wright Flyer Papers, ACSC hopes to encourage 

critical examination of the findings and to stimulate further 

research in these areas.

JAY H. LINDELL

Brigadier General, USAF

Commandant



Abstract

Ongoing casualties inflicted on convoys transgressing 

dangerous roads highlighted airlift’s important role in intratheater logistics operations within Iraq. While airlift can help 

decrease the number of convoys on the roads in combat 

zones, the finite number of airlifters must be managed effectively and efficiently to maximize its impact in supporting 

operations. This research proposes using a regional huband-spoke heuristic to design major-theater-war channel 

systems. The purpose of this research is to recommend a 

relaxation of the airlift operations’ doctrinal definition of the 

hub-and-spoke concept to allow for inclusion of a regional 

hub in-theater. 

To justify this recommendation, a case study methodology 

is used to compare performance of the intratheater airlift 

channel system as it existed in Iraq in February 2004 to a 

model channel system created using a regional hub heuristic. The two channel systems are compared using dependent 

variables designed to characterize efficiency, effectiveness, 

and adherence to the logistics principle of simplicity. The 

channel system created using a regional hub heuristic is 

more efficient by about 8 percent and more effective by 48 

percent. Comparisons of adherence to the logistics principle 

of simplicity are inconclusive.



Using an Intratheater Regional 

Hub Heuristic in Iraq 

An Exploratory Case Study

In November 2004, then chief of staff of the Air Force 

Gen John Jumper visited Iraq. Upon his return, he told a 

group of Washington writers that he “had a little fit” when 

he ascertained the lack of efforts to use intratheater airlift 

assets to their full potential to reduce ground convoys into 

Iraq.1 General Jumper stated that he helped create better 

communication between the joint force air component commander (JFACC) and the land commanders.2 Undoubtedly, 

he communicated his vision of an increased USAF role in 

transporting materiel by air, which would decrease the number of convoys and reduce the average of 100 casualties per 

month suffered by convoy personnel. A month later, General 

Jumper gladly reported that increased airlift operations to 

and within Iraq had decreased the number of convoys and 

taken 30 people per day off Iraq’s most dangerous roads.3

In the above example, the increase in airlift operations 

was a direct result of squeezing additional sorties from the 

already taxed C-130 Hercules fleet, as well as using the 

C-17 Globemaster to transport Army cargo. Additionally, 

the AF started flying cargo bound for Army and Marine 

ground units in western Iraq directly to those airfields with 

C-17s.4 The question then became, why, after almost three 

years of Operation Iraqi Freedom (OIF), was the USAF not 

leveraging every possible sortie it could muster to save lives 

by reducing ground convoys? More importantly, is there any 

way to further reduce ground convoys by more efficiently 

or effectively using airlift? Finally, are there any “lessons 

learned” to improve effectiveness, efficiency, or simplicity in 

using intratheater air in future campaigns?

Purpose of this Research

The purpose of this research is to recommend a change 

to air mobility doctrine. Current airlift doctrine confines the 

definition of hub-and-spoke. Air Force Doctrine Document 

(AFDD) 2-6, Airlift Operations, states,
Intertheater airland operations normally offload personnel and materiel at a main operating location within the theater. Subsequently, 

intratheater airlift moves designated personnel and equipment to 

forward operating locations, an employment concept referred to as a 

hub-and-spoke operation.5

This research recommends a relaxed doctrinal definition of 

hub-and-spoke operations to adopt a more inclusive definition of the concept that allows for subordinate intratheater 

or regional hubs. 

Statement of the Problem

Since the purpose of this research is to propose a change to 

existing doctrine, the objective addressed herein is to provide 

justification for this recommendation. This research therefore 

accomplishes an exploratory case study methodology comparing a snapshot (February 2004) of the channel airlift system servicing Iraq to a notional channel airlift routing system 

constructed using a regional hub heuristic. Dependent variables were compared using objective measures of efficiency 

and effectiveness and a subjective analysis of simplicity. The 

case study analysis seeks to justify this recommendation by 

demonstrating that the use of the regional hub-and-spoke 

heuristic to design a channel airlift system resulted in a more 

efficient, effective, and simple system.

Research Objectives

To accomplish the overall purpose of this research and 

justify the recommendation to relax the airlift doctrinal definition of hub-and-spoke operations, this effort was divided 

into logical steps, or research objectives.

Research Objective 1. The first portion of objective 1

was to understand the nature of US Central Command’s 

(USCENTCOM) channel airlift system, the scheduled theater 

airlift routing system (STARS), during the period of study. 

This required an exhaustive analysis and decomposition of 

utilization rates down to individual legs during the month 

of February 2004. For example, a C-130 travels from Al 

Udeid, Qatar, to Tallil, Iraq, to Baghdad, Iraq, to Mosul, Iraq, 

and then back to Al Udeid. This single day’s work of four 

legs represents one route. This route may be flown several 

times a week, so one way of measuring efficiency (utilization 

rates) would be to sum the utilizations of all the individual 
legs to arrive at aggregated route utilization. This would be 

helpful to airlift schedulers if they were thinking about cutting or increasing the frequency of an entire route. On the 

other hand, if airlift schedulers were redesigning routes, 

they would have to assess and manipulate individual leg 

utilizations rather than routes. To complete research objective 1, this research decomposed STARS routes into their 

component legs to present the frequency and utilization of 

each individual leg.

The next portion of research objective 1 was to use efficiency and effectiveness measures to set the baseline 

for systemwide STARS performance. First, leg utilization 

rates were aggregated as an efficiency measure for the entire STARS. Next, queue-days were calculated for each leg 

according to a constant, uniform demand assumption. Finally, individual leg queue-days were summed to measure 

and characterize STARS effectiveness.

Research Objective 2. The second objective was to design 

a new STARS adhering to a regional hub-and-spoke heuristic. The first challenge in designing the new STARS was to 

pick a regional hub within Iraq. Several assumptions were 

made about the utilization data; for example, that demand 

was constant and uniform. If a leg were flown from Baghdad 

to Mosul three times a week and the average utilization rate 

were seven people on each flight (21 people per week), then a 

constant, uniform demand assumption allows the researcher 

to conclude that three people need to travel from Baghdad to 

Mosul each day. The Methodology section of this work enumerates all assumptions made to design the new STARS. Of 

note, this research effort designed a new STARS by trial and 

error. In other words, the new STARS was developed without the aid of simulation or transportation network software, 

just as it would be done by in-theater airlift schedulers. 

Research Objective 3. The next phase of the research 

was to apply historical demand data to the new STARS and 

measure efficiency (systemwide utilization) and effectiveness 

(total queue-days) of the new STARS. Historical (February 

2004) data was used as a predictor of future demand.

Research Objective 4. The final phase of this research 

compared quantitative measures of effectiveness and efficiency between the CENTCOM’s February 2004 STARS (old 

STARS) and a STARS built using a regional hub-and-spoke 
heuristic while conforming to joint movement center (JMC) 

business rules (new STARS). Additionally, each system was 

compared qualitatively for adherence to the logistics principle of simplicity.

Research Questions

Given a STARS designed using a regional hub-and-spoke 

heuristic, three research questions were proffered:

1. Is the new hub-and-spoke STARS more efficient (higher 

utilization rate of C-130s) than the old STARS? 

2. Is the new STARS more effective (less queue-days) 

than the old STARS?

3. Does the new STARS better conform to the logistics 

principle of simplicity than the old STARS?

Scope 

The scope of this research was defined by two primary 

factors: duration and type of airlift. First, the data gathered 

for this study measures STARS utilization rates for 28 days 

in February 2004. This data was used primarily because 

it was available to the researcher. Additionally, this time 

period marks a stable use of one STARS system; that is, 

the STARS was not changed during this period. This period 

of time should reflect a somewhat stable period of sustainment, as it began almost a year after cessation of the maneuver combat period of OIF.

As previously noted, this research limited its analysis of 

effectiveness, efficiency, and simplicity to only the STARS or 

channel type of airlift system. This was necessary because 

each type of airlift (channel and demand-triggered) uses 

separate and distinct scheduling processes. A combined 

analysis of both types becomes unwieldy and beyond the 

time and space constraints of this research effort. However, 

conclusions reached in this study do put forward the possibility that a more effective, efficient, simpler channel system (STARS) may increase use of channel airlift, thus supplanting requirements for demand-triggered airlift. Given a 

reliable, predictable STARS, customers may be more willing 
to use it for high-priority cargo rather than requesting special onetime (demand-triggered) missions.

Limitations

The greatest limitations to this exploratory case study 

involve assumptions made to design and measure the new 

STARS performance. While all research assumptions are 

enumerated under Methodology below, one merits emphasis because it severely limits the power of any conclusions 

made by this research: that is the assumption that past 

demand data was constant and uniform and that future 

demand will mirror past demand.

In essence, this study tests a new regional hub heuristic 

STARS with the same data used to design the new STARS. 

Simultaneously, it handicaps the old STARS by not allowing 

it to improve its performance, given February’s data. A more 

realistic comparison would entail comparing the old STARS 

(updated with February’s data) against the hub heuristic 

STARS during the month of March. However, March data was 

not available. Next, the lack of raw data necessitated making 

a constant, uniform assumption about future demand. The 

only data available for this research was the mean monthly demand for each leg. For example, given a weekly flight between 

Mosul and Kirkuk, the raw data would include the utilization 

rate each week. Instead, the data available for this research 

consisted of only the average of all four weeks. Access to the 

raw data would facilitate building a more robust simulation 

model to account for variance instead of using averages. 

In summary, this research demonstrated the importance 

of efficiently using the intratheater airlift fleet and effectively 

meeting transportation requirements. Intratheater airlift in Iraq 

keeps convoys off the roads and saves lives. The following sections provide the background necessary to understand STARS 

(research objective 1), present efficiency and effectiveness measures of the old STARS to complete research objective 1, illustrate the methodology used to accomplish research objectives 2 

and 3 by designing and applying data to a new STARS, present 

the results of research objective 3, and accomplish dependent 

variable comparisons to accomplish research objective 4. Finally, results, future implications, and recommendations for 

future research are discussed. 
Background

This section is a review of literature and resources necessary to understanding the research problem and methodology used to answer the research questions. Major topics 

focus on the hub-and-spoke background, Iraq’s channel 

airlift system (STARS), and a discussion of each of the dependent variables (efficiency, effectiveness, and simplicity). 

Hub and Spoke

Research on hub networks abounds in academia and 

commercial sector literature. Utilizing one or more hubs 

within a distribution network allows consolidation of traffic flows for many types of transportation problems. Applications for the hub-and-spoke concept include movement 

of people, commodities, information, and energy. Research 

shows that effective utilization of hubs as transshipment 

points allows schedulers to bundle flows and reduce indirect connections to minimize systemwide costs and better 

utilize finite resources.6

Throughout the body of hub network literature, a great 

deal of research has attempted to optimize transportation 

network designs through operations management science 

techniques such as modeling, simulation, and enumeration. Each new journal article on this subject uses these 

techniques to find optimal or “near optimal” solutions to 

distribution problems. Successive research efforts build 

on previous ones by including one more heretofore nonincluded variable. New and complex algorithms are tailormade to solve specific, unique business problems. This 

complex field of optimizing distribution networks was best 

described in a 1994 research effort by two widely published 

professors in the field who observed that “prospects for a 

comprehensive model for hub-network optimization are 

limited at the moment.”7 Currently, there exists no off-theshelf equation or computer software flexible enough to account for all variables used in multiple military intratheater 

scheduling problems.

Without software or detailed techniques to help design 

intratheater transportation networks, military airlift schedulers use whatever knowledge they bring to the problem, to 

include past experience, lessons learned by their predeces-
sors, and airlift doctrine guidance.8 Instead of proactively 

designing an intratheater airlift network with systemwide 

optimization goals, schedulers may add routes as demanded 

and later optimize or tweak them reactively according to 

utilization data. This reactive process entails making effectiveness and efficiency trade-offs at the individual route or 

leg level rather than seeking a comprehensive systemwide 

optimization. As previously stated, this research seeks a 

change to airlift doctrine to provide future intratheater airlift schedulers with a simple hub heuristic to realize more 

efficient and effective large intratheater network designs.

Airlift operations doctrine defines the use of hub-andspoke operations as one type of airland employment concept. The other employment concept is direct delivery. As 

noted, current airlift doctrine only recognizes the hub as 

the point where intertheater meets intratheater. Employment of the hub-and-spoke concept as written entails cargo 

and passengers originating in another theater, arriving at 

the theater hub, and crossloading onto intratheater airlift 

for onward movement to forward operating locations (FOL). 

Conversely, the direct-delivery option would involve movement directly from another theater to the FOL, thereby bypassing the theater hub.9

A review of an Air Force Institute of Technology (AFIT) 

thesis, “Integrating C-17 Direct Delivery Airlift into Traditional Airlift Doctrine,” reveals that most theater airlift networks will most likely use a mixture of hub-and-spoke and 

direct-delivery employment concepts.10 Since this research 

effort limited its focus to the intratheater channel system 

servicing Iraq, direct delivery from other theaters to FOLs 

in Iraq was not explored. 

Channel Airlift Command and Control

Describing the Iraqi channel airlift system requires an 

explanation of the organizational structure which produces, monitors, and executes intratheater channel airlift. 

This section delineates the command and control structure 

for STARS and the responsibilities of stakeholders. 

Title 10, as amended by the Defense Reorganization Act of 

1986, states, “A geographic combatant commander has directive authority over logistics within his or her area of respon-
sibility.”11 In this case study, the commander, USCENTCOM 

exercised the option to stand up a joint movement center (JMC) 

to satisfy those responsibilities. According to Joint Publication 

(JP) 4-01.3, Joint Tactics, Techniques, and Procedures for Movement Control, the JMC is the “primary advisor to the combatant 

commander in the transportation apportionment process.”12

The JMC, through the combatant commander’s J-4 (joint 

logistics office) staff, acts as single coordination point for all 

theater movements, regardless of medium—air, land, or sea. 

Within the domain of air, the JMC validates requests for airlift 

and sets policy regarding STARS. The JMC works in coordination with the Air Mobility Division and director of mobility 

forces (DIRMOBFOR) on scheduling STARS to optimize efficiency and effectiveness. 

While the JMC acts as a single source for oversight of 

all common-user transportation assets, planned movement 

requirements, and movement policy, the airlift assets themselves are usually under the operational control (OPCON) of 

the commander, Air Force forces (COMAFFOR). In CENTCOM, 

the COMAFFOR has OPCON of C-130s and is dual-hatted 

as the JFACC. Figure 1 depicts command relationships 

relating to airlift. While not pictured in the figure, an air 

movement designator (AMD) is responsible for assisting the 

JMC in developing a STARS schedule, ensuring the schedule is included in the air tasking order (ATO), and acting as 

a focal point for collecting utilization data for each STARS 

route. The AMD would fit in the same place in the figure as 

the air mobility operations control center (AMOCC), which 

accomplishes essentially the same function served by the 

AMD. The DIRMOBFOR oversees operations and planning 

and coordinates between the JMC, US Transportation Command, various CENTCOM staff agencies, and the JFACC.13

Channel Airlift

 Airlift operations in Iraq are resource constrained by 

the number of intratheater C-130s available to accomplish 

force-sustainment logistics, deployment, and redeployment 

operations. During the period of this study (February 2004), 

CENTCOM had OPCON of 64 C-130s operating from four 

different locations. CENTCOM C-130s were dedicated to 

intratheater airlift operations in that area of responsibility 
(AOR) supporting OIF in Iraq, Operation Enduring Freedom 

(OEF) in Afghanistan, and Horn of Africa (HOA) operations. 

C-130s supporting OIF were based at either Ali Al Saleem 

(AAS), Kuwait, or Al Udeid Air Base, Qatar.14

Given the sheer magnitude of logistically supporting these 

three separate operations, it is no wonder that intratheater 

airlift contributes only a small percentage of what actually 

moves in any given week. To illustrate, each day the US 

COMMAND RELATIONSHIPS FOR AIR MOBILITY

FORCES ATTACHED TO A JOINT TASK FORCE

Theater

AFCC

AMOCC

Commander

Assigned

Attached

Air Force Forces

Theater Assigned

and Attached

Air Mobility Forces

US TRANSCOM

Air Mobility Forces

Support JTF

US TRANSCOM

Assigned

Air Mobility Forces

Air Mobility

Forces Attached

to the JTF

TACC

Commander

TACC

AMC

Commander

AMOCC

SECRETARY OF DEFENSE

GEOGRAPHIC

COMBATANT

COMMANDER

Commander,

USTRANSCOM

CJTF

COMAFFOR and/or JFACC

COMMAND COCOM OPCON COORD

AE

Cell

AE

Cell

AF

AFCC

AMC

AMOCC

COCOM

COMAFFOR

COORD

JFACC

JFC

JTF

OPCON

TACC

USTRANSCOM

Aeromedical Evacuation

Air Force Component Commander

Air Mobility Command

Air Mobility Operations Control

Center

Combatant Command

(Command Authority)

Commander, Air Force Forces

Coordination

Joint Force Air Component

Commander

Joint Force Commander

Joint Task Force

Operational Control

Tanker/Airlift Control Center

US Transportation Command

Figure 1. Notional command relationships for air mobility 

forces in a JTF. (Adapted from JP 3-17, Joint Tactics, Techniques, 

and Procedures for Air Mobility Operations, 14 August 2002, III-8.)
10

military in Iraq requires approximately 215 convoys consisting of 3,000 vehicles such as flatbed trucks, oil tankers, 

or heavy-equipment transports to sustain coalition forces. 

To put this in perspective, a C-130 can carry approximately 

two truckloads of cargo. This means it would take 1,500 

C-130s dedicated solely to OIF operations to match surface 

logistics efforts there.15 

Effectiveness. Airlift’s niche in the force-sustainment mission is speed. The trade-off inherent in using airlift revolves 

around speed versus capacity. That is, airlift can transport 

high-priority items quicker than ground convoys, but the 

quantity of items is limited by available airlift. To reconcile 

this, the USCENTCOM, through the JMC, designated transportation priorities for cargo to move on airlift.16 For instance, 

two supply classes, III (bulk fuel) and V (munitions), were 

designated low priorities for air movement. The large quantities of fuel and munitions needed for sustainment combined 

with the sheer bulk/weight of moving these supply classes 

make them a natural fit for ground convoy. Conversely, passengers and aircraft spare parts (class IX–air) were designated 

high priorities. 

Given an accurate prioritization system, one can assume 

that the intratheater airlift system is moving the right things 

(cargo or passengers). Furthermore, it is reasonable to assume that once these high-priority items enter the airlift system, units in Iraq need them delivered as soon as possible. 

Therefore, airlift effectiveness as measured in this research 

effort deals with the ability to transport items quickly; that 

is, to reduce intransit and/or wait times. For example, if an 

Apache helicopter belonging to an attack regiment of the 

101st Airborne Division in Mosul were not mission-capable 

for want of a part, the 101st would prefer the part travel by 

air from Kuwait for an in-transit/wait time of one day rather 

than travel four days by ground. However, if the 101st had 

to wait a week for a scheduled C-130 flight, the unit might 

choose to ground-ship the part. Thus, effectiveness emerges 

as the combination of waiting for transportation (queue-time) 

and in-transit time. Given the paucity of C-130s available to 

support OIF, it would seem the US military would utilize 

every C-130 bound for Iraq to its fullest allowable cabin load 

(ACL). Unfortunately, this was not the case during the period 

of this study, and thus the efficiency problem emerges.
11

Effectiveness versus Efficiency. In a letter of instruction 

(LOI) for intratheater airlift, CENTCOM, through the JMC, provided a “set of business rules to efficiently employ scarce airlift 

assets while providing a means to effectively meet the transportation needs of a variety of users throughout the AOR.”17

Throughout this LOI, CENTCOM’s business rules recognized 

implicit trade-offs for seeking optimization of efficiency goals versus optimization of effectiveness goals. For instance, using the 

previous Apache part example, if a C-130 flew to Mosul loaded 

with only the Apache part, we can see that effectiveness from 

the perspective of the 101st Airborne (the war fighter) would be 

high while efficiency (ACL utilization) would be low. Conversely, 

if the C-130 were forced to wait four days until it had a full load 

of cargo bound for Mosul, the opposite would hold—high efficiency, low effectiveness. This omnipresent trade-off between 

effectiveness and efficiency is well documented by research efforts within airlift and logistics communities. 

 To realize better efficiency and maintain acceptable levels of 

effectiveness, airlift doctrine prescribes a mix of several different 

mission-tasking categories of airlift. The categories according to 

doctrine include: channel, special assignment airlift missions, 

special air missions, air mobility express, joint airborne/air 

transportability training, and exercise/contingency.18 For the 

purposes of this research, these mission-tasking categories aggregate into two types of intratheater airlift—demand-triggered 

(onetime) and channel (recurring) airlift. To illustrate further, 

demand-triggered missions resemble calling a taxi, while the 

channel missions liken more to a regular bus schedule. The 

focus of this research is limited to channel-type airlift, more 

specifically the Iraqi STARS.

Several differences exist between demand-triggered and 

channel airlift. Channel airlift consists of a variety of routes, 

made up of one or more legs, flown on a scheduled basis to 

meet recurring, predictable demand on a requirements or frequency basis. Conversely, demand-triggered airlift consists 

of everything else—all nonrecurring transportation requirements. Demand-triggered missions may include deployments, 

redeployments, VIP movements, prisoners of war, aeromedical evacuations, high-visibility or backlogged cargo, and operational repositioning of troops and/or equipment.19 At one 

level, each of these demand-triggered missions represents a 

onetime, unpredictable demand for transportation. At a higher 
12

level, even these seemingly unpredictable demands aggregate 

and start to represent predictable patterns of demand. As a 

channel system matures, it should effectively satisfy predictable demand, given a certain level of efficiency (e.g., 50 percent 

utilization). Finally, demand-triggered airlift complements the 

channel airlift system by satisfying any demand exceeding the 

channel system’s capacity, or for assured effectiveness, call 

the taxi when the bus will not work.20

Demand-triggered missions increase system effectiveness by satisfying high-priority demand quicker than channel missions without regard to efficiency. For instance, assume a C-130 channel leg between Mosul and Kuwait that 

flies three times a week and averages 33 percent C-130 utilization each trip. Due to low utilization, airlift schedulers 

conclude this route does not meet the minimum 50 percent 

utilization threshold for continued service, per channel-airlift 

business rules. The business rules support a decision to cut 

the frequency of this channel leg from three times to twice 

per week, thereby increasing utilization (efficiency) to 50 

percent. If we assume constant, uniform demand, cutting 

the channel-leg frequency increases queue-time for units 

(cargo or passengers) transported on this leg and thereby 

decreases effectiveness. In our example, the customers 

(war fighters) are not happy with the decrease in frequency, 

but grudgingly admit it meets their transportation needs 

most of the time. However, occasionally they require highpriority transportation that either exceeds the capacity of this 

channel leg or cannot wait days until the next service. On 

these occasions, they may request demand-triggered airlift 

through the JMC. As long as their requests meet CENTCOM’s 

airlift request criteria, they will receive a onetime, demandtriggered air mission. This example illustrates use of channel airlift to meet a level of recurring demand at a given 

level of efficiency, augmented by demand-triggered airlift to 

achieve effectiveness. 

Iraq STARS Background

Before OIF, the JMC evaluated STARS missions once or twice 

per month as they serviced demand for OEF. After hostilities commenced for OIF, JMC evaluated and changed STARS 

at least weekly.21 As one might expect, the dynamic environ-
13

ment of maneuver operations led to the creation of an Iraqi 

STARS without the benefit of a known movement-demand 

history. To paraphrase one planner working in the JMC, many 

of the STARS built at this time were ad hoc, scheduled at 

the request of Army or Marine generals who were busy with 

immediate posthostility termination efforts. Requests for 

new STARS routes resulted in a schedule with 145 different 

STARS routes to service OEF, OIF, and HOA. As the air mobility 

division (AMD) schedulers assessed efficiency and cut inefficient routes, the number of STARS routes shrank from 145 in 

May 2003 to a total of 42 routes in February 2004.22 

Efficiency. In October 2003 this process of tweaking to 

cut inefficient routes was formalized by CENTCOM’s Intratheater Airlift Letter of Instruction. The LOI set minimum average requirements for C-130 utilization. Furthermore, the 

LOI provided a process whereby AMD could cut routes (with 

JMC approval) if they failed to meet these minimum average 

efficiency requirements. The only caveat to this was a “compelling minimum frequency requirement agreed to by both 

the JMC director and DIRMOBFOR.”23 As depicted in table 

1, minimum averages equated one pallet position to 10 passengers, enabling planners to convert cargo or passengers 

into a common unit by multiplying pallet-equivalents by a 

factor of 10. Of note, JMC set two pallets or 20 passengers 

(20 units) as the minimum threshold utilization for STARS 

performance and 40 units as a utilization goal/target.24

Pallets or Equivalent

Pallet Positions 

Passengers Monthly Average to 

Keep STARS Route?

2 0 Yes

1 And 10 or more Yes

0 And 20 or more Yes

Adapted from USCENTCOM, Intratheater Airlift Letter of Instruction, 15 October 2003, 9.

Both the JMC and AMD measured efficiency as a percentage of target rather than a percentage of the entire C-130 ACL. 

Therefore, the threshold of 20 units translates to 50 percent 

Table 1. Minimum STARS route averages 
14

of target versus the actual 33 percent of C-130 ACL. Through 

the remainder of this paper, utilization rates are expressed as 

a percentage of the target rate; the reader should remember 

that 50 percent utilization really means 50 percent of the 66 

percent target, or 33 percent of C-130 ACL. With these business rules in hand, AMD planners tweaked routes for efficiency gains from October 2003 every month leading up to the 

time of this research (February 2004). Efficiency gains came 

from cutting route frequency, changing routes, and even creating additional routes. While other efficiency measures (e.g., 

total air miles) are briefly discussed in the final section, this 

research effort used the same measure of efficiency as used 

by the JMC/AMD, C-130 target ACL utilization.

Simplicity. In addition to efficiency and effectiveness 

goals, channel airlift designs should also address ease of 

use by the customer. JP 4-0, Doctrine for Logistics Support 

of Joint Operations, designates simplicity as one of the principles of logistics. It states, “Simplicity reflects the need to 

reduce complexity and often fosters efficiency in both the 

planning and execution of national and theater logistics operations.”25 In other words, a channel-airlift system should 

adhere to the logistics principle of simplicity, at least in part 

because a simpler system may in turn make it easier for 

schedulers to make the system more efficient. Furthermore, 

from a war fighter’s perspective, a simpler to understand and 

use STARS may increase the war fighter’s propensity to use 

STARS versus demand-triggered airlift; that is, to use the 

bus instead of calling the taxi. Since no overarching quantitative variable exists for measuring simplicity, this research 

effort analyzed simplicity as a qualitative variable through 

subjective discussion. Final decisions as to whether the February 2004 STARS or the researcher-created new STARS 

was simpler are left for the reader to decide.

This section provided insight to understanding the research 

problem and the dependent variables presented in the research 

questions. Additionally it presented background information to 

provide a framework for understanding the STARS (research 

objective 1). The next section completes research objective 1 by 

describing the February 2004 STARS and measuring its performance against the dependent variables. It also describes the 

methodology used to design a new STARS (research objective 2) 

and measure its performance (research objective 3).
15

Methodology

This section revisits the research objectives and questions 

set forth earlier, then describes the methodology and results 

for research objective 1. Next, it lists the assumptions made 

to complete objective 2 and presents a complete methodology and results for completing that objective. Finally, it details the methodology for completing objective 3. Research 

objectives 3 and 4 results are presented in the next section.

Research objectives and questions are aligned with fulfilling the purpose of this research, as stated above. The overall 

problem emerges as whether using a regional hub-and-spoke 

heuristic to design a STARS results in a more efficient, effective, and simpler system, thereby justifying a less restrictive 

definition of the hub-and-spoke heuristic in airlift doctrine. 

To address this problem, four research objectives were created. Research objective 1 is to understand the old STARS. 

Next, research objective 2 is to design a new STARS adhering 

to the regional hub-and-spoke heuristic. Objective 3 tests 

the performance of the new STARS by applying the known 

demand data against the new schedule and measuring both 

effectiveness and efficiency. Finally, objective 4 compares results from research objectives 1 and 3 to assess effectiveness 

and efficiency and present a qualitative analysis of adherence to the logistics principle of simplicity.

Research Objective 1

All data and information regarding STARS routes during the 

month of February 2004 were provided by the AMD. At that 

time, the researcher was acting as the C-4 air transportation 

officer for Combined Joint Task Force Seven (CJTF 7) stationed at Camp Victory, Baghdad, Iraq. During that month, 

routes included service to five bases in Iraq. All Iraqi-bound 

STARS originated from either Al Udeid, Qatar, or Ali As Saleem, 

Kuwait. Another node serviced by the Iraq STARS was Kuwait 

City International Airport (KCIA), a mere 15 miles away from 

AAS. Al Udeid and KCIA acted as theater hubs, as the bulk of 

cargo and personnel supporting Iraq transited these traditional 

theater hubs. Once a week the Iraq STARS included service to 

Bahrain if cargo or passengers were awaiting transportation. If 

not, the C-130 on this route would overfly Bahrain on its way 

from Al Udeid to KCIA. 
16

The nine bases (or nodes) included in the STARS throughout February 2004 were Baghdad, Mosul, Tallil, Kirkuk, 

Balad, AAS, KCIA, Al Udeid, and Bahrain. As of February 

2004, nine different routes serviced these nodes. Table 2 depicts the nodes serviced (in order) by each of the different route 

packages. As illustrated, routes were flown a varying number 

of times each week, with one route operating four times per 

week and several routes only operating once per week. Each 

route represents one C-130 and crew flying each of the scheduled legs within one crew duty day. Twenty routes or 20 C-

130 missions were dedicated to fly the Iraq STARS each week. 

For instance, referencing Day 1 of table 2, one would expect 

three C-130s to fly STARS routes in support of Iraq. The first 

C-130 (Route A) would takeoff from its base at AAS to reposition at KCIA, where it would download any personnel or cargo 

bound for that station and upload personnel and cargo bound 

for Balad (its next station). This process would repeat through 

Balad, KCIA, Baghdad International Airport (BIAP), KCIA, and 

then the C-130 would return to base at AAS.

Efficiency. To complete research objective 1, table 2 routes 

were decomposed into their component legs for measurement. 

Average leg-utilization rates were provided by the AMD. Table 

3 depicts each of the legs flown by the STARS presented in 

table 2. 

The first column of table 3 (leg frequency per week) presents 

the number of times each week a particular leg was flown. The 

second and third columns depict the origin and destination of 

each individual leg. The fourth column, provided by the AMD, 

presents the average percent of target utilization of each of the 

legs throughout the month of February. It was calculated by 

taking the actual number of units loaded on each leg and dividing by the target of 40 units. Recall that since 40 units only 

represents two-thirds of a C-130 ACL (60 units), then percent 

utilization may total more than 100 percent, as illustrated by 

the KCIA-to-Balad route. The fifth column was calculated by 

the researcher using the following formula:

40 units (percent of target) X (frequency per week) 

= weekly demand

Finally, the sixth column was calculated by dividing weekly 

demand by seven and rounding. Summing weekly demands 

gives the average number of units per week moved by the Iraq 
17

Table 2. Old STARS schedule

Route A Route B Route C

Day 1

AAS

KCIA

Balad

KCIA

Baghdad

KCIA

AAS

Al Udeid

(Bahrain)

Kuwait

Mosul

Baghdad

Balad

Al Udeid

Al Udeid

Tallil

Balad

Baghdad

Al Udeid

Route D Route E Route F

Day 2

AAS

KCIA

Tallil

Mosul

KCIA

AAS

Al Udeid

KCIA

Mosul

Kirkuk

KCIA

Al Udeid

Al Udeid

KCIA

Baghdad

KCIA

Al Udeid

Route A Route C Route G Route H

Day 3

AAS

KCIA

Balad

KCIA

Baghdad

KCIA

AAS

Al Udeid

Tallil

Balad

Baghdad

Al Udeid

Al Udeid

KCIA

Mosul

Baghdad

KCIA

Al Udeid

Al Udeid

KCIA

Balad

Kirkuk

KCIA

Al Udeid

Route D

Day 4

AAS

KCIA

Tallil

Mosul

KCIA

AAS

Route A Route C Route F Route H Route I

Day 5

AAS

KCIA

Balad

KCIA

Baghdad

KCIA

AAS

Al Udeid

Tallil

Balad

Baghdad

Al Udeid

Al Udeid

KCIA

Baghdad

KCIA

Al Udeid

Al Udeid

KCIA

Balad

Kirkuk

KCIA

Al Udeid

Al Udeid

KCIA

Baghdad

Mosul

KCIA

Al Udeid

Route D Route E Route G

Day 6

AAS

KCIA

Tallil

Mosul

KCIA

AAS

Al Udeid

KCIA

Mosul

Kirkuk

KCIA

Al Udeid

Al Udeid

KCIA

Mosul

Baghdad

KCIA

Al Udeid

Route A

Day 7

AAS

KCIA

Balad

KCIA

Baghdad

KCIA

AAS
18

STARS throughout the month of February 2004. This sum 

was 2,326 units. Recall that one pallet position or 10 passengers converts to 10 units. Therefore, Iraq’s STARS moved 

2,326 passengers per week or 232.6 pallet-equivalents per 

week, or some mixture of the two. 

Due to the constant, uniform demand assumption, the efficiency for the entire February STARS was easily determined. 

Each “percent of target” utilization rate was multiplied by its 

corresponding “leg frequency per week,” and then summed. 

This sum was divided by the total legs per week (99) to determine the overall STARS efficiency. The overall efficiency meaFrequency 

Per Week Depart Arrive

% of Target 

(40 units)

Weekly 

Demand

Daily 

Demand

10 Al Udeid KCIA 222.5 290 12.9

10 KCIA Al Udeid 230.0 120 17.1

9 BIAP KCIA 292.5 333 47.6

7 KCIA AAS 227.5 221 23.0

7 AAS KCIA 212.5 235 25.0

7 KCIA BIAP 125.0 350 50.0

6 KCIA Balad 122.5 294 42.0

5 KCIA Mosul 105.0 210 30.0

4 Balad KCIA 292.5 148 21.1

4 Mosul KCIA 255.0 288 12.6

4 Kirkuk KCIA 245.0 272 10.3

3 Tallil Balad 247.5 257 28.1

3 Mosul BIAP 222.5 227 23.9

3 Balad BIAP 245.0 254 27.7

3 Tallil Mosul 267.5 281 11.6

3 KCIA Tallil 127.5 153 21.9

3 Al Udeid Tallil 232.5 239 25.6

3 BIAP Al Udeid 257.5 269 29.9

2 Mosul Kirkuk 237.5 230 24.3

2 Balad Kirkuk 225.0 220 22.9

1 BIAP Mosul 287.5 235 25.0

Table 3. February 2004 STARS leg frequencies and efficiency
19

sure (percent of target utilization rate) for the February 2004 

STARS was 58.74 percent; meaning that on average, any individual leg of the AMD’s STARS utilized 58.74 percent of the 

40-unit target. Put another way, any given C-130 carried an 

average of 23.5 passengers or 2.35 pallet-equivalents. 

Effectiveness. Another portion of research objective 1 was 

to measure the effectiveness of the February 2004 STARS. 

Effectiveness equaled the total number of queue-days across 

the system in a state of equilibrium for one week. In-transit 

days were ignored, as all flights were completed in less than 

one day. Table 4 depicts the manual methodology used in 

this research to calculate total number of queue-days. The 

methodology consisted of applying the constant, uniform 

daily-demand rate (from table 3) to each of the legs. Given 

the STARS schedule presented in table 2, units of demand 

were either cleared (value = 0) each day or accumulated until 

a scheduled flight satisfied demand.

Table 4 provides a summary of effectiveness by depicting 

the number of units in each leg-queue by day. Columns 

1, 2, and 3 should be familiar, as they mirror table 3. The 

units collected in each daily leg-queue represent a steady 

state; that is, the queue quantity measured in the second 

and all succeeding weeks. For instance, take the KCIA-to-Al 

Udeid leg (in table 4). Since no flight exists to service this 

leg on Day 1 (table 2), the daily-demand rate of 17.1 units 

(table 3) accumulates in Week 1. The model reaches equilibrium in Week 2 when the unsatisfied demand from Day 

7 is added to the Day 1 demand for a total of 34.2 units 

awaiting transportation. Therefore, the STARS attains equilibrium in the second and all succeeding weeks. 

Through-loading was allowed at the KCIA hub. In other 

words, unit demand to or from Al Udeid was satisfied by 

routes which took that demand through KCIA first. This 

assumption helped STARS effectiveness measures for legqueue demand for Al Udeid to Tallil and BIAP to Al Udeid. 

To further illustrate, passengers/cargo bound for Tallil 

from Al Udeid could “deadhead” on flights from Al Udeid 

to Kuwait and then on to Tallil instead of waiting for direct 

flights from Al Udeid to Tallil. This assumption was consistent with KCIA operations as a theater hub.

Since the unsatisfied demand in each daily leg-queue 

was expressed in common units, the entire spreadsheet 
20

(table 4) was summed to arrive at a weekly expression of 

unsatisfied demand. This sum represents the number of 

passengers or pallet-equivalent (multiplied by 10) queuedays awaiting transportation; that is, the measure of effectiveness for this research. The sum for table 4 was 1,194.9

unit queue-days. Therefore, given the assumptions already 

made, we could expect 1,194.9 passenger queue-days or 

119.49 pallet-equivalent queue-days. Another way to conceptualize this sum is to say that 100 passengers or 10 pallets awaited transportation for 11.949 days, while all other 

demand was satisfied within one day.

Research Objective 2

The second objective was to design a new STARS adhering to a regional hub-and-spoke heuristic. This section 

Table 4. February 2004 STARS effectiveness

Depart Arrive

Daily

Demand

Day 

1

Day 

2

Day 

3

Day 

4

Day 

5

Day 

6

Day 

7

Al Udeid KCIA 12.9 — — — 12.9 — — 12.9

KCIA Al Udeid 17.1 34.2 — — 17.1 — — 17.1

BIAP KCIA 47.6 — — — 47.6 — — —

KCIA AAS 23.0 — — — — — — —

AAS KCIA 25.0 — — — — — — —

KCIA BIAP 50.0 — — — 50.0 — 50.0 40.0

KCIA Balad 42.0 226.0 48.0 — 42.0 — 42.0 24.0

KCIA Mosul 30.0 — 30.0 — — 30.0 — 30.0

Balad KCIA 21.1 — 21.1 — 21.1 — 21.1 —

Mosul KCIA 12.6 25.2 — 12.6 — — — 12.6

Kirkuk KCIA 10.3 20.6 — — 10.3 — — 10.3

Tallil Balad 28.1 — 28.1 — 28.1 — 28.1 16.2

Mosul BIAP 23.9 27.8 11.7 — 23.9 27.8 — 23.9

Balad BIAP 27.7 — 27.7 — 27.7 — 27.7 15.4

Tallil Mosul 11.6 23.2 — 11.6 — 11.6 — 11.6

KCIA Tallil 21.9 43.8 25.7 27.6 — 21.9 — 21.9

Al Udeid Tallil 25.6 — — — 25.6 — — 25.6

BIAP Al Udeid 29.9 — 29.9 — 29.9 — — 29.9

Mosul Kirkuk 24.3 24.3 — 24.3 28.6 12.9 — 24.3

Balad Kirkuk 22.9 28.7 12.6 — 22.9 — 22.9 25.8

BIAP Mosul 25.0 15.0 20.0 25.0 30.0 — 25.0 10.0
21

describes the methodology used to design the new STARS 

starting with several assumptions made to begin design.

Assumption 1: Constant, Uniform Demand. As previously mentioned, this assumption was necessary due to 

the lack of raw data; however, this assumption represents 

a limitation to this study. The constant portion assumes 

demand does not change due to the day of the week or even 

time of the year. The uniform portion of the assumption 

simplifies the calculations required to measure dependent 

variables but discounts the effects caused by variance in 

demand. Modeling the variability associated with demand 

would give schedulers the ability to simulate future demand 

against a schedule and thereby build better schedules.

Assumption 2: Future Demand Mirrors Past Demand. 

This acts as a simplifying assumption to complete a comparison of the two STARS. Not enough information exists 

to predict future STARS demand with anything other than 

past demand.

Assumption 3: Demand Would Transfer. This assumption was crucial to the creation of a regional hub in Iraq. This 

assumption means that when intra-Iraq legs were cancelled 

to adhere to a pure hub heuristic, there would be no change 

in demand. For example, when the Kirkuk-to-Mosul leg was 

cut, it was assumed that this leg-demand would transfer in 

total to the Kirkuk-to-Balad and Balad-to-Mosul legs.

Assumption 4: No Unknown Operational Limitations.

This assumption encompasses all of the unknowns, which 

would not reveal themselves in the course of a research 

paper but would in practice. This includes problems with 

securing slot times at airfields, ability to execute the new 

schedule, and logistical constraints. Special care was taken 

to use no more C-130s per week from any one station (AAS or 

Al Udeid) than the February 2004 STARS. Furthermore, the 

new schedule stays within nautical mileage and numberof-legs limits represented by the February STARS. These 

limits were 1,603 nautical miles (nm) and a total of six legs 

for any one route.

Assumption 5: Right of Through-loading and Sameday Cross-loading at Hubs. This assumption was used to 

assess effectiveness of the February 2004 STARS as well. 

This assumption was expanded from the hub at KCIA to 

incorporate a regional hub within Iraq at Balad. Through-
22

loading allows cargo/passengers to remain manifested on a 

C-130 as it arrives and departs a hub. Cross-loading consists of cargo/passengers deplaning at the hub and then 

boarding another flight, which is the reason hubs are called 

hubs. The same-day component of cross-loading simply 

means that cargo bound for Kirkuk can be unloaded at 

Balad from a C-130 which originated at KCIA and then put 

on a flight for Kirkuk that same day. This research effort 

did not complete a STARS schedule down to the hour, so 

this assumption acts as a simplifying assumption, which 

may in practice present new scheduling problems.

Assumption 6: Balad is Able to Act as a Regional 

Hub. As stated below in the first design step, Balad was 

selected as a regional hub. This assumption acted as a simplifying assumption to facilitate building the new STARS 

model. To actually make Balad a regional channel hub 

would consider many logistics issues such as throughput 

capacity, parking and loading constraints, availability of 

materiel-handling equipment, and manpower. 

Design Step 1. The first step was picking a regional 

hub in Iraq. Balad was selected for three reasons. Both 

Balad and BIAP were considered due to their central location between the other Iraqi air bases and represent the 

first and second, respectively, greatest amount of weekly 

demand when compared to all other Iraqi bases. In fact, 

BIAP’s demand (units originating from or destined for) exceeded Balad’s by over 1,200 units. While BIAP could just 

as easily have been selected, the final decision was made 

due to practical considerations. In practice, Balad acts as a 

ground logistics hub for the Army in Iraq. This final factor 

led to the decision to use Balad as the hub for this study. 

Design Step 2. The second step was to determine the 

total number of flights (legs) required to satisfy demand at 

each of the individual nodes. Of note, the data in table 3 

was used to guide the entire new STARS design process. 

First, total weekly demand entering and departing each 

node was figured. For instance, weekly demand for Mosul 

totaled 336 units inbound and 145 units departing. Each 

of these totals was divided by the maximum C-130 ACL (60 

units). Thus Mosul requires six C-130s to meet inbound 

demand and only three to satisfy outbound demand. Since 

all planes landing at Mosul must take off the same day, one 
23

can begin to see the inefficiency inherent in the imbalance 

between inbound and departing demands. Repeating this 

process for each airfield produced the minimum number of 

flights necessary to service each node.

Design Step 3. The third step in the design was to determine a new leg structure adhering to a pure regional 

hub-and-spoke heuristic. First, all non-Balad, intra-Iraq 

legs were eliminated. Then, daily demand from each of the 

eliminated legs was routed through Balad. So Mosul-toBIAP demand would now be satisfied by two legs: first a 

Mosul-to-Balad leg and a same-day Balad-to-BIAP leg. This 

process was repeated and used to amend the number of 

required legs. 

Design Step 4. Next, flights from KCIA and Al Udeid to each 

of the Iraq bases were assessed to determine if efficiencies could 

be gained by routing those legs through the regional hub (Balad) 

first. This resulted in routing KCIA-to-Mosul through Balad. 

Similarly, Al Udeid-to-Tallil and BIAP-to-Al Udeid demand was 

routed through KCIA to take advantage of through-loading at 

the KCIA hub. Finally, cuts were made to the Kirkuk-to-KCIA 

leg due to its inefficient performance and failure to meet JMC’s 

50 percent efficiency threshold. Inefficient positioning legs (i.e., 

AAS-to/from-KCIA and Al Udeid-to/from-KCIA) were not considered for cuts. These positioning legs were considered part of 

the cost of doing business, as they represent inefficiency caused 

by C-130 basing. Positioning from the C-130 base at AAS to the 

theater hub at KCIA was unavoidably inefficient from a utilization perspective but could not be helped unless C-130 basing 

was changed. Basing changes were beyond the scope of this 

research. The design process aimed to keep the number of legs 

in the new STARS (103) relatively close to the number of legs in 

the old STARS (99). 

Design Step 5. After determining the number of required 

legs to service each node, the next step was to build a new 

weekly STARS schedule. The daily-demand rate served as 

a guide for spacing legs throughout the week. Route design 

was iteratively trial and error, using effectiveness and efficiency as feedback. The first iteration of scheduling resulted 

in a total of 16 missions with very high efficiency and effectiveness on par with the old STARS. This lower number of 

missions was expected since required legs had been figured 

using the full C-130 capacity (60 units). At this point, three 
24

Route A

Day 1

AAS

KCIA

BIAP

KCIA

Balad

KCIA

AAS

Route A Route B Route C

Day 2

AAS

KCIA

BIAP

KCIA

Balad

KCIA

AAS

Al Udeid

KCIA

Tallil

Balad

KCIA

Al Udeid

Al Udeid

KCIA

Balad

Mosul

KCIA

Al Udeid

Route D Route E

Day 3

Al Udeid

KCIA

BIAP

Balad

BIAP

KCIA

Al Udeid

Al Udeid

KCIA

Balad

Mosul

Balad

Al Udeid

Route A Route F Route G

Day 4

AAS

KCIA

BIAP

KCIA

Balad

KCIA

AAS

AAS

KCIA

Tallil

Balad

Mosul

KCIA

AAS

Al Udeid

KCIA

Balad

Kirkuk

KCIA

Al Udeid

Route H Route I

Day 5

Al Udeid

KCIA

Balad

BIAP

KCIA

Al Udeid

Al Udeid

KCIA

Balad

Mosul

Balad

Al Udeid

Route F Route I Route J

Day 6

AAS

KCIA

Tallil

Mosul

KCIA

AAS

Al Udeid

KCIA

Balad

Mosul

Balad

Al Udeid

AAS

KCIA

BIAP

KCIA

BIAP

KCIA

AAS

Route F Route G Route I Route K Route L

Day 7

AAS

KCIA

Tallil

Balad

Mosul

KCIA

AAS

Al Udeid

KCIA

Balad

Kirkuk

KCIA

Al Udeid

Al Udeid

KCIA

Balad

Mosul

Balad

Al Udeid

Al Udeid

KCIA

BIAP

Balad

KCIA

Al Udeid

Al Udeid

Balad

BIAP

Balad

KCIA

Al Udeid

Table 5. New STARS schedule
25

missions were added to gain effectiveness. Refer to table 5 to 

view the new STARS. A total of 12 routes was created, flying 19 

C-130 missions (saving one C-130) and 103 legs (four more 

than the old STARS).

Research Objective 3 Methodology

The same methodology was used to calculate and measure 

efficiency and effectiveness for the new STARS as was used in 

objective 2 for the old STARS. The goal of objective 3 was to 

apply the demand data to the new STARS. This involved creating rationales according to the design assumptions as to what 

would happen to demand when some of the old STARS legs 

were cut. Table 6 details these rationales, which detail how 

the original demand data was applied to the new STARS legs. 

In sum, table 6 depicts the flow of cargo/passengers through 

the new STARS system, and it acted as an input to calculating new STARS efficiency and effectiveness. The next section 

presents efficiency and effectiveness measurements/results 

for the new STARS and compares these to the old STARS.

Results

This section presents the results for research objectives 3 

and 4. It begins with a presentation of the efficiency of the new 

STARS and compares this to the old STARS. Next, it presents 

new STARS effectiveness results and compares those results 

to old STARS effectiveness. It concludes with an analysis of 

adherence to the principle of simplicity of both STARS.

Research Objectives 3 and 4 Results

Efficiency. As noted, calculating efficiency and effectiveness 

for the new STARS followed the same methodology as in research objective 1 for the old STARS. Table 7 depicts efficiency/

utilization rates for both STARS legs. For legs in common to 

both STARS, efficiency/utilization increased for six of the new 

STARS legs, remained the same for three, and decreased for 

four. Not counting the positioning/depositioning legs, the old 

STARS had six underperforming (below 50 percent of target 

utilization) legs; the new STARS only one. 

As in research objective 1, total system efficiency was 

calculated for the new STARS by weighting each of the leg 
26

Depart Arrive

Old

frequency

per week

New

frequency

per week

Rationale for 

demand/frequency changes

Al Udeid KCIA 10 11 Al Udeid-Tallil demand added to this leg

KCIA Al Udeid 10 8 Added BIAP-Al Udeid demand to this leg

BIAP KCIA 9 7

Days 1–6 BIAP-Al Udeid demand added 

to this leg. On day 7 BIAP-KCIA demand 

added to BIAP-Balad-KCIA routes

KCIA AAS 7 7 No change

AAS KCIA 7 7 No change

KCIA BIAP 7 7 On day 7 KCIA-BIAP demand added 

KCIA-Balad-BIAP route

KCIA Balad 6 11 KCIA-Mosul demand added to this leg

KCIA Mosul 5 0 This leg cancelled. Demand added to 

KCIA-Balad and Balad-Mosul legs

Balad KCIA 4 6 On day 7 BIAP-Al Udeid demand added 

to this leg

Mosul KCIA 4 4 No change

Kirkuk KCIA 4 2 Frequency decreased due to inefficient 

performance

Tallil Balad 3 4 Tallil-Mosul demand added to this leg

Mosul BIAP 3 0 This leg cancelled. Demand added to 

Mosul-Balad and Balad-BIAP legs

Balad BIAP 3 3 Added Mosul-BIAP demand to this leg

Tallil Mosul 3 0 This leg cancelled. Demand added to TallilBalad and Balad-Mosul legs

KCIA Tallil 3 4 Al Udeid-Tallil demand added to this leg

Al Udeid Tallil 3 0 This leg cancelled. Demand added to Al 

Udeid-KCIA leg

BIAP Al Udeid 3 0

This leg cancelled. On days 2–6 demand 

through/cross loads on BIAP-KCIA-Al 

Udeid route. On day 7 demand added to 

BIAP-Balad-KCIA-Al Udeid route

Mosul Kirkuk 2 0 This leg cancelled. Demand added to 

Mosul Balad and Balad-Kirkuk legs

Balad Kirkuk 2 2 Mosul-Kirkuk demand added to this leg

BIAP Mosul 1 0 This leg cancelled. Demand added to new 

BIAP-Balad and Balad-Mosul legs

BIAP Balad 0 3

On day 7 added BIAP-KCIA and BIAP-Al 

Udeid demand. Added BIAP-Mosul demand to this new leg

Mosul Balad 0 4 Added Mosul-Kirkuk and Mosul-BIAP 

demand to this new leg

Balad Mosul 0 8

Added Tallil-Mosul, BIAP-Mosul, and KCIAMosul demand to this leg. Other added 

flights needed to balance flights out

Balad Al Udeid 0 4 Added flights for depositioning

Al Udeid Balad 0 1 Added flight for positioning

Table 6. Leg frequency/week comparison and demand rationale
27

Old

Frequency 

per week

New 

Frequency 

per week

Depart Arrive Old Daily 

Demand

Old 

Weekly 

Demand

New 

Daily

Demand

New 

Weekly 

Demand

Old 

% of 

Targert

New 

% of 

Target

10 11 Al Udeid KCIA 12.9 490 18.4 129.0 422.5 429.3

10 8 KCIA Al Udeid 17.1 120 27.0 189.0 430.0 453.0

9 7 BIAP KCIA 47.6 333 49.3 344.8 492.5 119.6

7 7 KCIA AAS 43.0 421 43.0 421.0 447.5 447.5

7 7 AAS KCIA 45.0 435 45.0 435.0 412.5 412.5

7 7 KCIA BIAP 50.0 350 42.9 300.0 125.0 107.1

6 11 KCIA Balad 42.0 294 72.0 504.0 122.5 114.5

5 0 KCIA Mosul 30.0 210 Route Cut 105.0 NA

4 6 Balad KCIA 21.1 148 22.6 157.9 492.5 465.8

4 4 Mosul KCIA 12.6 488 12.6 488.0 455.0 455.0

4 2 Kirkuk KCIA 10.3 472 10.3 472.0 445.0 490.0

3 4 Tallil Balad 48.1 457 19.7 138.0 447.5 486.3

3 0 Mosul BIAP 43.9 427 Route Cut 422.5 NA

3 3 Balad BIAP 47.7 454 11.6 481.0 445.0 467.5

3 0 Tallil Mosul 11.6 481 Route Cut 467.5 NA

3 4 KCIA Tallil 21.9 153 27.4 192.0 127.5 120.0

3 0 Al Udeid Tallil 45.6 439 Route Cut 432.5 NA

3 0 BIAP Al Udeid 49.9 469 Route Cut 457.5 NA

2 0 Mosul Kirkuk 44.3 430 Route Cut 437.5 NA

2 2 Balad Kirkuk 42.9 420 47.1 450.0 425.0 462.5

1 0 BIAP Mosul 45.0 435 Route Cut 487.5 NA

0 3 BIAP Balad New Route 14.6 102.4 NA 485.3

0 4 Mosul Balad New Route 48.1 457.0 NA 435.6

0 8 Balad Mosul New Route 46.6 326.0 NA 101.9

0 4 Balad Al Udeid New Route

Positioning 40.0 0 NA 440.0

0 1 Al Udeid Balad New Route

Depositioning 40.0 0 NA 440.0

Table 7. Old and news STARS efficiency comparisons

percent utilizations (multiplying by frequency) and then 

summing these. The sum was divided by total number of 

legs (103) to determine the system percentage of target utilization. The overall efficiency measure (percentage of target utilization rate) for the new STARS was 66.93 percent. 

This was 8.19 percent more efficient than the old STARS’ 

58.74 percent utilization rate. Additionally, the new STARS 

makes better use of the crew duty day by adding four legs 

to the total STARS, while simultaneously cutting one aircraft mission for a total of 19 missions versus the 20 routes 

flown by the old STARS. To further ensure validity, flight 

mileage for both STARS was compared; all distances were 
28

calculated using the baseops.net flight calculator. Execution of the new STARS entails flying a total of 25,816 nm 

versus the old STARS’ 26,915 nm. Additionally, the longest 

route executed in the new STARS was 1,590 nm compared 

to 1,603 nm in the old STARS. There was only a 13 nm 

difference in average route length between the old STARS 

(1,346 nm) and the new STARS (1,359 nm). 

Effectiveness. Effectiveness or total queue-days for the 

new STARS was calculated following the same methodology 

used to calculate effectiveness for the old STARS in research 

objective 1, Table 8 depicts the spreadsheet used to calculate 

unit queue-days for each leg. The new STARS schedule (table 5) 

was used in conjunction with the new projected daily-demand 

rates to manually calculate the queue-days for each grid in 

table 8. Again, demand was either cleared each day or accumulated, according to the new STARS schedule. Throughand cross-loading were allowed through the hubs (Al Udeid, 

KCIA, and now Balad). The new STARS reached equilibrium 

(steady state) in the first week, as all demand was cleared 

on Day 7. Unit queue-days were summed for the entire system. The sum of queue-days for new STARS in table 8 was 

622.9 unit queue-days compared to the old STARS’ 1,194.9. 

This represents a 48 percent reduction in unit queue-days. To 

conceptualize this, recall that 2,326 units traveled per week 

in the old STARS. If these were passengers, the effectiveness 

measure means that passengers using the new STARS would 

travel on the day they wanted to travel 73 percent of the time, 

thus waiting a day only 27 percent of the time. Comparatively, 

passengers would wait for transportation 51 percent of the 

time in the old STARS and only travel on the day they wanted 

to travel 49 percent of the time.

Simplicity. Research question 3 asked which STARS adheres 

more to the logistics principle of simplicity. Since no quantitative, definitive answer to this question exists, the question merits 

a simple qualitative comparison of the two STARS. As alluded to 

earlier, a simple STARS design is easier to use and execute and 

could result in increased use as the war fighter becomes more 

apt to take the bus than call a taxi. STARS simplicity (or lack of 

it) derives from the schedule and ultimately the heuristics behind the schedule. 

If one simply compares the two schedules from tables 

2 and 5, the new STARS appears just as complicated, if 
29

not more so, than the old one. The new STARS uses more 

routes (11) than the old STARS (nine). Furthermore, if one 

looks at the schedules from the perspective of a passenger 

trying to get from point A to point B, both schedules appear 

complicated. However, armed with the knowledge of which 

locations act as hubs, thus allowing through-loading and 

cross-loading, passengers can quickly form a plan to get to 

their destination. 

Seeing the schedule through an educated passenger’s 

eyes demonstrates the flexibility and effectiveness of the new 

STARS over the old one. For example, a passenger needing 

to fly from Baghdad to Mosul could travel direct on the old 

STARS only on Day 6. If the passenger knew that KCIA and 

Al Udeid acted as hubs, the passenger could fly to the KCIA 

hub on any day except Day 4 and then travel from KCIA to 

Mosul on Days 2, 5, and 7. Under the new STARS, the same 

passenger could not travel direct; however, given the knowlDepart Arrive Daily 

Demand Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7

Al Udeid KCIA 18.4 18.4 –– –– –– –– 18.4 ––

KCIA Al Udeid 27.0 27.0 –– –– –– –– 27.0 ––

BIAP KCIA 49.3 –– –– –– –– –– –– ––

KCIA AAS 43.0 –– –– 43.0 –– 43.0 –– ––

AAS KCIA 45.0 –– –– 43.0 –– 43.0 –– ––

KCIA BIAP 42.9 –– –– –– –– –– –– ––

KCIA Balad 72.0 12.0 –– 12.0 –– –– 12.0 ––

Balad KCIA 22.6 –– –– 22.6 –– 22.6 45.2 ––

Mosul KCIA 12.6 12.6 –– 12.6 –– 12.6 –– ––

Kirkuk KCIA 10.3 10.3 20.6 30.9 –– 10.3 20.6 ––

Tallil Balad 19.7 19.7 –– 19.7 –– 19.7 –– ––

Balad BIAP 11.6 11.6 23.2 –– 11.6 –– 11.6 ––

KCIA Tallil 27.4 27.4 –– 27.4 –– 27.4 –– ––

Balad Kirkuk 47.1 47.1 14.2 21.3 –– 47.1 14.2 ––

BIAP Balad 14.6 14.6 29.2 –– 14.6 29.2 43.8 ––

Mosul Balad 48.1 48.1 16.2 –– 48.1 –– –– ––

Balad Mosul 46.6 46.6 33.2 19.8 46.4 –– –– ––

Balad Al Udeid 40.0 –– –– –– –– –– –– ––

Al Udeid Balad 40.0 –– –– –– –– –– –– ––

Table 8. New STARS effectiveness
30

edge of the existence of hubs, the passenger could travel direct to Balad on Days 2 and 7 then on to Mosul; or to KCIA 

on any day except Day 7; KCIA to Balad on Days 2, 4, 5, and 

7; and finally from Balad to Mosul on any day except Day 1. 

While not overtly simpler, the key to simplifying passengers’ 

travel plans is to educate them on the existence of the hubs. 

Air transportation experts making passengers’ reservations 

can advise them on the hubs and reserve the connections. 

While the new STARS schedule may not appear overtly 

simpler, especially to passengers attempting to travel between 

Iraqi locations, the heuristic of a regional hub in Iraq creates a 

simpler cognitive map for those charged with executing STARS 

as a network. Figures 2 and 3 below illustrate the legs in the 

old and new STARS. Arrows indicate direction of travel; in 

many cases legs were one-way. The simplicity manifested by 

creating a Balad hub in the new STARS allows transportation 

personnel to adopt a transport strategy of “get it to Balad.” 

A qualitative assessment of the transportation networks 

illustrated by figures 2 and 3 reveals the new STARS as a 

simpler design. However, due to the complexity of the new 

STARS schedule, this research effort stops short of definiBalad

Mosul Kirkuk

BIAP

KCIA

AAS

Tallil

Al Udeid

Figure 2. Old STARS
31

tively stating which STARS more closely adheres to the logistics principle of simplicity. Therefore, the qualitative results for research question 3 were inconclusive. Instead, 

the research aims to put the question to the reader. As a 

passenger, a unit trying to ship cargo, a transportation specialist routing cargo throughout Iraq, or an AMD scheduler responsible for making monthly improvements to the 

STARS, which STARS design is preferable?

Summary

This section began by presenting utilization rates (efficiency) and total unit queue-days (effectiveness) as measured after applying historical demand data to the new 

STARS, which was designed using a regional-hub heuristic 

at Balad. Results revealed the new STARS as more efficient 

and significantly more effective than the old STARS. Next, it 

presented a qualitative analysis of both STARS’ adherence 

to the logistics principle of simplicity. Results were inconclusive. Instead, the simplicity analysis presented adequate 

information to allow the reader to decide subjectively which 

STARS was simpler. The final section discusses the impliKirkuk

Mosul Balad Tallil

Al Udeid BIAP

KCIA

AAS

Figure 3. New STARS
32

cations of these findings in relation to the purpose of this 

research and future efforts.

Conclusion

This section first discusses the implications of the results presented above. The individual research questions 

are restated and answered, the results adequately justify 

the recommendation to relax the USAF doctrinal definition 

of the hub-and-spoke concept to allow for the possibility 

of intratheater regional hubs, and recommendations are 

made to help guide future research. 

Implications of Results

Due in large part to the limitations mentioned earlier, 

this exploratory case study falls well short of definitively 

proving that using a regional hub heuristic will always result in a more efficient, effective, and simpler channel-airlift 

system. Notwithstanding these limitations, caused by the 

constant/uniform demand assumption, the results for this 

individual case study present a compelling case for at least 

further exploring utilization of a regional hub for the STARS 

in Iraq. To illustrate this, revisit the research questions.

1. Is the hub-and-spoke (new) STARS more efficient 

(higher utilization rate of C-130s) than the old 

STARS? 

2. Is the new STARS more effective (less queue-days) 

than the old STARS?

3. Does the new STARS better conform to the logistics 

principle of simplicity than the old STARS?

Within this case study, the answers to research questions 

1 and 2 were yes, the STARS employing the hub heuristic 

was more efficient and more effective. Results from research 

question 3 were inconclusive—that is to say, picking the 

STARS which more closely conforms to the logistics principle 

of simplicity was subjective. Determining which STARS was 

simpler depends on the perspective of the person making 

the judgment. While an airlift scheduler might be inclined to 

think the new STARS was simpler, a potential STARS pas-
33

senger desiring to travel to and from locations within Iraq 

might deem the old STARS schedule to be simpler. This passenger would notice that seven direct routes were cut in the 

new STARS schedule thereby necessitating additional travel 

through Balad. 

Given the results of this case study, airlift schedulers 

would be remiss if they did not further explore the possible 

benefits of incorporating a hub heuristic into their STARS 

design. Furthermore, USAF doctrine should change to allow 

employing an intratheater, regional hub to sustain major 

regional conflicts like OIF. The doctrine should state that 

during major theater operations, if several forward operating locations exist within a geographical region separated 

by some distance from the theater hub, then schedulers 

should consider employing a subordinate regional hub for 

hub-and-spoke operations. 

Although the power of the results presented in this case 

study was limited by the validity of the data, the research 

indicates a potential for STARS designs using a regional 

hub heuristic to result in gains in both effectiveness and 

efficiency. If an improved STARS design results in C-130 

mission savings, as was the case for the new STARS, then 

those saved C-130 missions could help reduce ground convoys in Iraq and, according to General Jumper, save lives. 

Recommendations to Future Researchers

Several topics emerged during the course of this research 

which beg for follow-on research. The first of these deals 

with overcoming the limitations inherent in the assumption of constant, uniform demand data. Secondly, review of 

similar industry regional-hub case studies reveals opportunities in repositioning resources (C-130s) and using optimization techniques to develop a process for determining the 

optimal location for a regional hub. Finally, the research 

process revealed a need to standardize and automate processes for schedule design and upkeep of an intratheater 

channel system.

Overcoming Limitations. A disciplined collection of 

STARS demand data would allow researchers to model 

STARS demand and run simulations to compare STARS design methodologies. Repeated simulations would lend valid-
34

ity to comparing STARS performance results. If demand were 

accurately modeled by individual leg distributions, researchers could simulate repeated runs of a STARS to accomplish 

sensitivity analysis on dependent variables like utilization 

(efficiency) and queue-time (effectiveness). Ideally, a simulation construct could be created to allow AMD schedulers 

to simply input data and test various iterations of proposed 

STARS schedules.

C-130 Basing and Hub Location. The second topic for 

future research entails more fully exploring opportunities 

to optimize resource (aircraft) and hub locations. Future researchers should explore effects on effectiveness and efficiencydependent variables by manipulating independent variables: 

C-130 basing and hub location. For example, imagine the possible increases to effectiveness measures in this case study 

had several C-130s been stationed at Balad. This would have 

allowed more legs per mission within the Iraqi region, possibly increasing effectiveness, given the reduction in mileage. 

Coincidentally, near the end of the research process for this 

case study, CENTCOM changed C-130 basing; eight C-130s 

were based at Balad, Iraq. The CENTAF commander, Lt Gen 

Walter Buchanan, in a February 2006 interview, commented 

that due to the C-130 moves to Balad that it has become a 

“true hub and spoke system.”26 The new STARS schedule incorporating the new basing of C-130s at Balad was not available to include in this research. While it is likely that the new 

schedule does not follow a pure hub heuristic in Iraq (i.e., 

no intra-Iraq flights unless routed through Balad), putting C-

130s at Balad combined with General Buchanan’s comments 

lends credibility to the recommendation to relax airlift doctrine to allow for regional hubs.27 Additionally, while this case 

study walked the reader through a decision process for picking the hub location (Balad) for the new STARS design, future 

research could formalize and improve on the decision process 

presented here.

Standardize and Automate STARS Design. Conversations with AMD and JMC personnel revealed a need to standardize STARS scheduling techniques and the benefits of 

developing software to make the airlift scheduler’s task easier. While industry equivalents use proprietary management 

information systems to optimize transportation routing, the 

USAF lacks a system to perform intratheater channel airlift 
35

scheduling. Investment in research and development of such 

a system could allow the USAF to realize a return on investment if that system improved utilization and effectiveness of 

intratheater channel airlift systems in the future. 

Summary

This exploratory case study fulfilled its purpose of testing 

the performance of a channel system designed with a regional 

hub heuristic to justify a recommendation for a change to airlift 

doctrine. The new STARS, designed using Balad as a regional 

hub, outperformed the old STARS in efficiency and effectiveness measures while simplicity results were inconclusive. 

However, assumptions made about the data used to compare 

STARS performance dilutes the validity of the results and detracts from the power of the conclusions. More research is required to improve validity of future STARS comparisons. This 

paper therefore made recommendations for future research to 

explore hub and resource location strategies, as well as standardizing scheduling processes through automation. 

Notes

1. John A. Tirpak, “Airlift Reduces Convoy Numbers; QDR and Tactical 

Aviation: Corrosion’s True Cost . . . More Airlift, Fewer Convoys,” Air Force 

Magazine 88, no. 2 (February 2005).

2. Ibid.

3. TSgt Don Nelson, “Increased C-130, C-17 Flights Relieve Army 

Ground Convoys,” Air Force Print News, 15 December 2004.

4. Ibid.

5. AFDD 2-6, Air Mobility Operations, 25 June 1999, 39.

6. M. E. O’Kelly and H. J. Miller, “The Hub Network Design Problem,” 

Journal of Transport Geography 2, no.1, 1994: 31.

7. Ibid.

8. Maj Keith Justice (JMC air transportation officer, November 2003–

April 2004), telephone and e-mail interviews by author, February–March 

2006.

9. AFDD 2-6.1, Airlift Operations, 13 November 1999, 15–17.

10. Maj Creighton W. Cook, “Integrating C-17 Direct Delivery Airlift 

into Traditional Air Force Doctrine” (master’s thesis, AFIT, Wright-Patterson 

AFB, OH, June 1998), 1–10.

11. JP 4-01.3, Joint Tactics, Techniques, and Procedures for Movement 

Control, 9 April 2002, 1-3. 

12. Ibid., 3-1.

13. Ibid., 3-1–2; and JP 3-17, Joint Tactics, Techniques, and Procedures 

for Air Mobility Operations, 14 August 2002, 3.

14. Justice, interviews.
36

15. Tom Squitieri, “Air Force Boosts Number of Supply Flights,” USA 

Today, 14 December 2004.

16. USCENTCOM, Intratheater Airlift Letter of Instruction, 15 October 

2003.

17. Ibid.

18. AFDD 2-6, Airlift Operations, 25 June 1999, 19.

19. Ibid., 19–23. 

20. USCENTCOM, Letter of Instruction; and JP 4-01.3, Joint Tactics, 

Techniques, and Procedures. 

21. Maj Mark A. Brown, “The Joint Movement Center: Manager of Iraqi 

Freedom Theater Airlift” (masters thesis, AFIT, Wright-Patterson AFB, OH, 

May 2004), 60. 

22. Justice, interviews; and information provided by Air Mobility Division personnel while the researcher was in-theater. 

23. USCENTCOM, Letter of Instruction, 9. 

24. Ibid. 

25. JP 4-0, Doctrine for Logistic Support of Joint Operations, 6 April 

2000, 2-1–2. 

26. Bruce Rolfsen, “Demobilizations Spur War-Zone C-130 Reductions,” Air Force Times, 6 March 2006, 18.

27. Bruce Rolfsen, “Numbers Soar for Close-air Sorties, Airlifts,” Air 

Force Times, 3 April 2006, 12.
37

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