bluuebunny/crossref_metadata_2025 huggingface dataset:
Managing a Retailer's Shelf Space, Inventory, and Transportation
Authors: Cachon Gerard
Published: December 2003

Retailers must constantly strive for excellence in operations; extremely narrow profit margins leave little room for waste and inefficiency. This article reports a retailer's challenge to balance transportation, shelf space, and inventory costs. A retailer sells multiple products with stochastic demand. Trucks are dispatched from a warehouse and arrive at a store with a constant lead time. Each truck has a finite capacity and incurs a fixed shipping cost, no matter the number of units shipped. There is a per unit shelf-space cost as well as holding and backorder penalty costs. Three policies are considered for dispatching trucks: a minimum quantity continuous review policy, a full service periodic review policy, and a minimum quantity periodic review policy. The first policy ships a truck when demand since the previous shipment equals a fixed fraction of a truck's capacity, i.e., a minimum truck utilization. The exact analysis of that policy is the same as the analysis of reorder point policies for the multiechelon problem with one-warehouse, multiple retailers, and stochastic demand. That analysis is not computationally prohibitive, but the minimum quantity level can be chosen with a simple economic order quantity (EOQ) heuristic. An extensive numerical study finds the following: Either of the two periodic review policies may have substantially higher costs than the continuous review policy, in particular when the warehouse to store lead time is short; the EOQ heuristic performs quite well; the minimum quantity policy's total cost is relatively insensitive to the chosen transportation utilization, and its total cost is close to a lower bound developed for this problem.
Optimizing Inventory Replenishment of Retail Fashion Products
Authors: Fisher Marshall , Rajaram Kumar , Raman Ananth
Published: December 2003

We consider the problem of determining (for a short lifecycle) retail product initial and replenishment order quantities that minimize the cost of lost sales, back orders, and obsolete inventory. We model this problem as a two-stage stochastic dynamic program, propose a heuristic, establish conditions under which the heuristic finds an optimal solution, and report results of the application of our procedure at a catalog retailer. Our procedure improves on the existing method by enough to double profits. In addition, our method can be used to choose the optimal reorder time, to quantify the benefit of leadtime reduction, and to choose the best replenishment contract.
Agility in Retail Banking: A Numerical Taxonomy of Strategic Service Groups
Authors: Menor Larry J. , Roth Aleda V. , Mason Charlotte H.
Published: December 2003

This research demonstrates that operations agility—defined as the ability to excel simultaneously on operations capabilities of quality, delivery, flexibility, and cost in a coordinated fashion—is a viable option for retail banks encountering increasing environmental change. The question of whether there is empirical evidence that services, specifically retail banks, display the characteristics of agility like their manufacturing counterparts is open to debate. Conventional wisdom in operations management posits that most successful services trade off one capability for another. Drawing from the resource-based view of the firm, combinative capabilities view, and the cybernetics work of Ashby (1958), theoretical arguments suggest the contrary. The agility paradigm is viable in environments calling for a mix of strategic responses. Applying cluster analytic techniques to a sample of retail banks, using capabilities as taxons, we identify four strategic service groups: agile, traditionalists, niche, and straddlers. Our empirical results provide thematic explanations consistent with theory that account for how the agile strategic group offers a unique configuration of service concept, resource competencies, strategic choices, and business orientation. Profiles of the operations strategies of each strategic service group suggest that each group has found a fit between what certain segments of the market may want and what they have to offer. In particular, we found that the agile group exhibited greater resource competencies than its counterparts, requiring greater investments in infrastructure and technology. Consistent with theory, agile banks performed better over time on an absolute measure of return on assets.
Selling to the Newsvendor: An Analysis of Price-Only Contracts
Authors: Lariviere Martin A. , Porteus Evan L.
Published: December 2003

We consider a simple supply-chain contract in which a manufacturer sells to a retailer facing a newsvendor problem and the lone contract parameter is a wholesale price. We develop a mild restriction satisfied by many common distributions that assures that the manufacturer's problem is readily amenable to analysis. The manufacturer's profit and sales quantity increase with market size, but the resulting wholesale price depends on how the market grows. For the cases we consider, we identify relative variability (i.e., the coefficient of variation) as key: As relative variability decreases, the retailer's price sensitivity decreases, the wholesale price increases, the decentralized system becomes more efficient (i.e., captures a greater share of potential profit), and the manufacturer's share of realized profit increases. Decreasing relative variability, however, may leave the retailer severely disadvantaged as the higher wholesale price reduces his profitability. We explore factors that may lead the manufacturer to set a wholesale price below that which would maximize her profit, concentrating on retailer participation in forecasting and retailer power. As these and other considerations can result in a wholesale price below what we initially suggest, our base model represents a worst-case analysis of supply-chain performance.
Coordinating Independent Buyers in a Distribution System to Increase a Vendor's Profits
Authors: Wang Qinan
Published: December 2003

We study the coordination of a two-echelon distribution system where a vendor distributes a single product to a set of independent buyers. The problem is analyzed as a Stackelberg game in which the vendor acts as the leader and buyers act as followers. A simple strategy is developed for the vendor to employ a uniform quantity-discount policy to coordinate buyers' replenishment times by the power-of-two policy. Solution procedures are developed for the equilibrium strategy. It is shown that time coordination generally has a substantial benefit for the vendor, although the benefit to the buyers may be limited. Furthermore, uniform quantity discounts to all buyers are normally feasible but not sufficient to achieve perfect channel coordination when buyers act independently. The proposed strategy obtains a high proportion of the maximum benefit under perfect channel coordination.
A Survey of Mathematical Programming Applications in Integrated Steel Plants
Authors: Dutta Goutam , Fourer Robert
Published: December 2003

Mathematical programming techniques were used in the steel industry as early as 1958, and many applications of optimization in steel production have been reported since then. In this survey, we summarize published applications in the largest steel plants by type, including national steel planning, product-mix optimization, blending, scheduling, set covering, and cutting stock.
Dynamic Capacity Expansion Problem with Deferred Expansion and Age-Dependent Shortage Cost
Authors: Hsu Vernon Ning
Published: December 2003

Deferring capacity expansion may be a cost effective decision when there is anticipation of cheaper capacity in the near future and/or the current demand is too low to justify an immediate expansion. This paper studies a finite-horizon capacity expansion problem (CEP) with deferred capacity expansion. The operating cost and the cost of holding unused capacity in each period depend on the time when the capacity is acquired, and the shortage cost depends on the time when the shortage occurred. Our model is a generalization of the Wagner-Whitin formulation of the CEP and an extension (with deferred expansion) of two other polynomially solvable CEPs in the literature. We explore structural properties of the problem and develop an efficient dynamic programming algorithm to solve the problem in polynomial time.
Gaining Benefits from Joint Forecasting and Replenishment Processes: The Case of Auto-Correlated Demand
Authors: Aviv Yossi
Published: December 2003

In this paper we consider a cooperative, two-level supply chain consisting of a retailer and a supplier. As in many practical settings, the supply chain members progressively observe market signals that enable them to explain future demand. The demand itself evolves according to an auto-regressive time series. We examine three types of supply chain configurations. In the first setting, the retailer and the supplier coordinate their policy parameters in an attempt to minimize systemwide costs, but they do not share their observations of market signals. In the second setting, resembling many original vendor-managed inventory (VMI) programs, the supplier takes the full responsibility of managing the supply chain's inventory, but the retailer's observations of market signals are not transferred to him. In our third setting, reminiscent of collaborative forecasting and replenishment partnerships, inventory is managed centrally, and all demand related information is shared. We propose a set of stylized models to study the three settings and use them to provide managerial insights into the value of information sharing, VMI, and collaborative forecasting.
Inventory-Service Optimization in Configure-to-Order Systems
Authors: Cheng Feng , Ettl Markus , Lin Grace , Yao David D.
Published: December 2003

This study is motivated by a process-reengineering problem in personal computer (PC) manufacturing, i.e., to move from a build-to-stock operation that is centered around end-product inventory towards a configure-to-order (CTO) operation that eliminates endproduct inventory. In fact, CTO has made irrelevant the notion of preconfigured machine types and focuses instead on maintaining the right amount of inventory at the components. CTO appears to be the ideal operational model that provides both mass customization and a quick response time to order fulfillment. To quantify the inventory-service trade-off in the CTO environment, we develop a nonlinear optimization model with multiple constraints, reflecting the service levels offered to different market segments. To solve the optimization problem, we develop an exact algorithm for the important case of demand in each market segment having (at least) one unique component, and a greedy heuristic for the general (nonunique component) case. Furthermore, we show how to use sensitivity analysis, along with simulation, to fine-tune the solutions. The performance of the model and the solution approach is examined by extensive numerical studies on realistic problem data. We present the major findings in applying our model to study the inventory-service impacts in the reengineering of a PC manufacturing process.
Coordination and Flexibility in Supply Contracts with Options
Authors: Barnes-Schuster Dawn , Bassok Yehuda , Anupindi Ravi
Published: December 2003

We investigate the role of options (contingent claims) in a buyer-supplier system. Specifically using a two-period model with correlated demand, we illustrate how options provide flexibility to a buyer to respond to market changes in the second period. We also study the implications of such arrangements between a buyer and a supplier for coordination of the channel. We show that, in general, channel coordination can be achieved only if we allow the exercise price to be piecewise linear. We develop sufficient conditions on the cost parameters such that linear prices coordinate the channel. We derive the appropriate prices for channel coordination which, however, violate the individual rationality constraint for the supplier. Contrary to popular belief (based on simpler models) we show that credit for returns offered by the supplier does not always coordinate the channel and alleviate the individual rationality constraint. Credit for returns are useful only on a subset of the feasibility region under which channel coordination is achievable with linear prices. Finally, we demonstrate (numerically) the benefits of options in improving channel performance and evaluate the magnitude of loss due to lack of coordination.
The Supply Chain Impact of Smart Customers in a Promotional Environment
Authors: Huchzermeier Arnd , Iyer Ananth , Freiheit Julia
Published: December 2003

Increasing product variety through the use of alternate package sizes is a commonly observed mechanism in the grocery industry. Under such a scheme, however, the response to pricing decisions for each of the different package sizes is affected by how customers make demand choices. We build a demand model in which customers react smart to retail promotions through stockpiling and package size switching. The demand model combines a customer choice model with a model in which customers differ in their stockpiling and reservation price levels. We utilize data from the German grocery industry for an empirical fitting of the model. We then develop a store-level inventory model for each SKU and optimize price promotions to maximize expected profit. We show the benefit of capturing the smart customer response to price promotions by demonstrating its impact on the reduced inventory costs. We use the model to generate a number of managerial implications of the model for the German grocery environment.
Coordinating Replenishment and Pricing in a Firm
Authors: Li Qing , Atkins Derek
Published: December 2003

Replenishment and pricing strategies are traditionally determined by entirely separate units of a firm, the former by production and the latter by marketing. In a large organization production and marketing are traditionally measured in terms of performance criteria appropriate and relevant within the world in which they operate, rather than in terms of overall company performance. We consider a situation where the headquarters uses a simple linear transfer price between the two functions to govern the transactions. The misaligned incentives among these functional managers are caused by a transfer price between them that distorts the marginal production cost and revenue, as well as by a misallocation of cost: Marketing's pricing strategy influences expected leftover inventory, but only production incurs the cost. The misalignment can be mitigated through the following two ways. First, if production commits to a service level instead of an inventory level, both production and marketing, and hence the firm as a whole, are better off. Second, the same improvement can be achieved through organizational changes so that marketing becomes the dominant function. We also propose a mechanism that aligns the functional managers' incentives to be compatible to the firm.
Performance Analysis of Split-Case Sorting Systems
Authors: Johnson M. Eric , Meller Russell D.
Published: December 2003

Split-case sorting systems are used in many retail supply chains where items must be distributed in less-than-case quantities, such as orders shipped directly to customers by catalogers and e-tailers or shipments made in less-than-case quantities from a distribution center to a retail store. These systems are particularly effective in order-packing systems where the same item is needed for multiple orders. Items are inducted into a circular sorting conveyor system one unit at a time and then delivered to an order-packing bin designated for a particular customer or retail store. We develop analytical performance models that incorporate the stochastic operating conditions faced by these systems. Our model allows system designers to predict the sorting capacity for different system configurations. More importantly, we use the model to develop insight into the system design and operation.
Multilocation Combined Pricing and Inventory Control
Authors: Federgruen Awi , Heching Aliza
Published: December 2003

We consider the problem of managing inventories and dynamically adjusting retailer prices in distribution systems with geographically dispersed retailers. More specifically, we analyze the following single item, periodic review model. The distribution of demand in each period, at a given retailer, depends on the item's price according to a stochastic demand function. These stochastic demand functions may vary by retailer and by period. The replenishment process consists of two phases: In some or all periods, a distribution center may place an order with an outside supplier. This order arrives at the distribution center after an “order leadtime” and is then, in the second phase, allocated to the retailers. Allocations arrive after a second “allocation leadtime.”

We develop an approximate model that is tractable and in which an optimal policy of simple structure exists. The approximate model thus provides analytically computable approximations for systemwide profits and other performance measures. Moreover, the approximate model allows us to prove how various components of the optimal strategy (i.e., prices and order-up-to levels) respond to shifts in the model parameters, e.g., to shifts in the retailers' demand functions. In addition, we develop combined pricing, ordering, and allocation strategies and show that the system's performance under these strategies is well gauged by the above approximations. We use this model to assess the impact of different types of geographic dispersion on systems with dynamically varying prices and how different system parameters (e.g., leadtimes, coefficients of variation of individual retailers' demand, price elasticities) contribute to this impact. Similarly, we use the model to gauge the benefits of coordinated replenishments under dynamic pricing, and how these benefits increase as the allocation decisions of the systemwide orders to individual retailers are postponed to a later point in the overall replenishment leadtime.

We report on a comprehensive numerical study based on data obtained from a nationwide department store chain.
Newsvendor Networks: Inventory Management and Capacity Investment with Discretionary Activities
Authors: Mieghem Jan A. Van , Rudi Nils
Published: December 2003

We introduce a class of models, called newsvendor networks, that allow for multiple products and multiple processing and storage points and investigate how their single-period properties extend to dynamic settings. Such models provide a parsimonious framework to study various problems of stochastic capacity investment and inventory management, including assembly, commonality, distribution, flexibility, substitution and transshipment. Newsvendor networks are stochastic models with recourse that are characterized by linear revenue and cost structures and a linear input-output transformation. While capacity and inventory decisions are locked in before uncertainty is resolved, some managerial discretion remains via ex-post input-output activity decisions. Ex-post decisions involve both the choice of activities and their levels and can result in subtle benefits. This discretion in choice is captured through alternate or “nonbasic” activities that can redeploy inputs and resources to best respond to resolved uncertain events. Nonbasic activities are never used in a deterministic environment; their value stems from discretionary flexibility to meet stochastic demand deviations from the operating point.

The optimal capacity and inventory decisions balance overages with underages. Continuing the classic newsvendor analogy, the optimal balancing conditions can be interpreted as specifying multiple “critical fractiles” of the multivariate demand distribution; they also suggest appropriate measures for and trade-offs between product service levels. This paper shows that the properties of optimal newsvendor network solutions extend to a dynamic setting under plausible conditions. Indeed, we establish dynamic optimality of inventory and capacity policies for the lost sales case. Depending on the nonbasic activities, this also extends to the backordering case. Analytic- and simulation-based solution techniques and graphical interpretations are presented and illustrated by a comprehensive example that features discretionary input commonality and a flexible processing resource.
Product Differentiation and Capacity Cost Interaction in Time and Price Sensitive Markets
Authors: Boyaci Tamer , Ray Saibal
Published: December 2003

In this paper, we study a profit-maximizing firm selling two substitutable products in a price and time sensitive market. The products differ only in their prices and delivery times. We assume that there are dedicated capacities for each product and that there is a standard industry delivery time for the regular (slower) product. The objective of the firm is to determine the delivery time of the express (faster) product and appropriately price the two products, taking into consideration the impact of delivery time reduction on capacity requirements and costs. We develop a model that integrates pricing and delivery time decisions with capacity requirements and costs, and study scenarios where the firm is constrained in capacity for none, one, or both product(s). We show how product differentiation decisions are influenced by capacity costs, and how the firm should adapt its differentiation strategy in response to a change in its operating dynamics. We first identify a market characteristic that governs the optimal pricing structure. We then show that the degree of product differentiation depends on both the absolute, as well as the relative values of the capacity costs. Provided that the capacity cost differential remains the same, higher capacity costs induce less time differentiation and less price differentiation. An increase in capacity cost differential increases price differentiation, but decreases time differentiation. The optimal prices depend, in addition to the above, on the market characteristic. We find that prices can actually decrease when the firm incurs capacity-related costs. We also explore the impact of substitutability on product differentiation, and illustrate our results in a numerical study.
Properties of the Periodic Review (R, T) Inventory Control Policy for Stationary, Stochastic Demand
Authors: Rao Uday S.
Published: December 2003

This paper compares the commonly used periodic review, replenishment interval, order-up-to (R, T ) policy to the continuous review, reorder point, order quantity, (Q, r) model. We show that long-run average cost function for the single-product (R, T ) policy has a structure similar to that of the (Q, r) model. Consequently, many of the useful properties of the latter model are applicable. In particular, the optimal cost is insensitive to the choice of the replenishment interval, T, provided the optimal order-up-to level, R, corresponding to T is used. For instance, a suboptimal T obtained from a deterministic analysis increases costs by no more than 6.125%. For continuous demand, we analytically prove that use of a (R, T)policy instead of the optimal policy increases costs by at most 41.42% in the worst case. Computational experiments on Poisson demand demonstrate that the average-case relative error of using a (R,T)policy is under 7.5%. This relative error is lower when the demand rate and leadtime are high and the fixed order costs are either very low or very high. When coordination of order placement epochs is desirable, the (R,T) policy may sometimes be preferred to the (Q, r) policy. In this context, we illustrate application of our single-product results to more complex systems. In particular, we show that a simple power-of-two, (R,T) based heuristic for the stochastic multiproduct joint replenishment problem has a worst-case performance guarantee of 1.5. A similar result is explored for a special case of a two-echelon serial inventory system
Optimal Replenishment Policies for Multiechelon Inventory Problems Under Advance Demand Information
Authors: Gallego Guillermo , Özer Özalp
Published: December 2003

Customers and downstream supply chain partners often place, or can be induced to place, orders in advance of future requirements. We show how to optimally incorporate advance demand information into periodic-review, multiechelon, inventory systems in series. While the state space for series systems appears to be formidably large, we decompose the problem across locations, as in Clark and Scarf (1960), and reduce the state space at each location by using modified echelon inventory positions (that nets known requirements). We prove the optimality of state-dependent, echelon base-stock policies for finite and infinite horizon problems. We also show that myopic policies are optimal and very easy to compute when costs and demands are stationary. We provide managerial insights into the value of advance demand information through a numerical study.
On the Interface Between Operations and Human Resources Management
Authors: Boudreau John , Hopp Wallace , McClain John O. , Thomas L. Joseph
Published: December 2003

Operations management (OM) and human resources management (HRM) historically have been very separate fields. In practice, operations managers and human resource managers interact primarily on administrative issues regarding payroll and other matters. In academia, the two subjects are studied by separate communities of scholars publishing in disjoint sets of journals, drawing on mostly separate disciplinary foundations. Yet, operations and human resources are intimately related at a fundamental level. Operations are the context that often explains or moderates the effects of human resource activities such as pay, training, communications, and staffing. Human responses to OM systems often explain variations or anomalies that would otherwise be treated as randomness or error variance in traditional operations research models. In this paper, we probe the interface between operations and human resources by examining how human considerations affect classical OM results and how operational considerations affect classical HRM results. We then propose a unifying framework for identifying new research opportunities at the intersection of the two fields.
The Effectiveness of Several Performance Bounds for Capacitated Production, Partial-Order-Service, Assemble-to-Order Systems
Authors: Dayanik Savas , Song Jing-Sheng , Xu Susan H.
Published: December 2003

We consider an assemble-to-order (ATO) system: Components are made to stock by production facilities with finite capacities, and final products are assembled only in response to customers' orders. The key performance measures in this system, such as order fill rates, involve evaluation of multivariate probability distributions, which is computationally demanding if not intractable. The purpose of this paper is to develop computationally efficient performance estimates. We examine several ideas scattered in diverse literatures on approximations for multivariate probability distributions, and determine which approach is most effective in the ATO application. To do so, we first tailor different approximation ideas to the ATO setting to derive performance bounds, and then compare these bounds theoretically and numerically. The bounds also allow us to make connections between capacitated and uncapacitated ATO systems and gain various insights.
Stigler's Diet Problem Revisited
Authors: Garille Susan Garner , Gass Saul I.
Published: December 2003

We review Stigler's diet problem, its impact on linear programming and operations research, and we determine minimum cost diets using updated nutritional and cost data. We also discuss how Stigler's diet problem formulation and its extensions have, over the years, influenced dietitians and nutritionists in their search for more wholesome but cost-effective diets.
Two Dimensional Rendezvous Search
Authors: Anderson Edward J. , Fekete Sándor P.
Published: December 2003

We consider rendezvous problems in which two players move on the plane and wish to cooperate to minimise their first meeting time. We begin by considering the case where both players are placed such that the vector difference is chosen equiprobably from a finite set. We also consider a situation in which they know they are a distance d apart, but they do not know the direction of the other player. Finally, we give some results for the case in which player 1 knows the initial position of player 2, while player 2 is given information only on the initial distance of player 1.
Inventory Policies for Systems with Stochastic and Deterministic Demand
Authors: Sobel Matthew J. , Zhang Rachel Q.
Published: December 2003

We consider a periodic review inventory system with demand arriving simultaneously from a deterministic source and a random source. The deterministic demand has to be satisfied immediately and the stochastic demand can be backordered. Assuming that the stochastic demand is never backlogged if there is stock in the system, we prove that a modified (s, S) policy is optimal under general conditions if there is a setup cost. If there is a smoothing cost instead of the setup cost, we observe that the problem corresponds to a standard model with one source of demand.
Scheduling a Major College Basketball Conference—Revisited
Authors: Henz Martin
Published: December 2003

Nemhauser and Trick presented the problem of finding a timetable for the 1997/1998 Atlantic Coast Conference (ACC) in basketball. Their solution, found with a combination of integer programming and exhaustive enumeration, was accepted by the ACC.

Finite-domain constraint programming is another programming technique that can be used for solving combinatorial search problems such as sports tournament scheduling. This paper presents a solution of round-robin tournament planning based on finite-domain constraint programming. The approach yields a dramatic performance improvement, which makes an integrated interactive software solution feasible.
Combining Minsum And Minmax: A Goal Programming Approach
Authors: Carrizosa Emilio , Romero-Morales Dolores
Published: December 2003

A number of methods for multiple-objective optimization problems (MOP) give as solution to MOP the set of optimal solutions for some single-objective optimization problems associated with it. Well-known examples of these single-objective optimization problems are the minsum and the minmax. In this note, we propose a new parametric single-objective optimization problem associated with MOP by means of Goal Programming ideas. We show that the minsum and minmax are particular instances, so we are somehow combining minsum and minmax by means of a parameter. Moreover, such parameter has a clear meaning in the value space. Applications of this parametric problem to classical models in Locational Analysis are discussed.
A Note on Coefficient Adjustment Using Sos Constraints
Authors: Lougee-Heimer R.
Published: December 2003

We examine two coefficient adjustment methods proposed in the literature, and we show by example that the second is not valid. We provide a modified approach that subsumes both methods, generalizing the first and correcting the second.
The Dynamic and Stochastic Knapsack Problem with Random Sized Items
Authors: Kleywegt Anton J. , Papastavrou Jason D.
Published: December 2003

A resource allocation problem, called the dynamic and stochastic knapsack problem (DSKP), is studied. A known quantity of resource is available, and demands for the resource arrive randomly over time. Each demand requires an amount of resource and has an associated reward. The resource requirements and rewards are unknown before arrival and become known at the time of the demand's arrival. Demands can be either accepted or rejected. If a demand is accepted, the associated reward is received; if a demand is rejected, a penalty is incurred. The problem can be stopped at any time, at which time a terminal value is received that depends on the quantity of resource remaining. A holding cost that depends on the amount of resource allocated is incurred until the process is stopped. The objective is to determine an optimal policy for accepting demands and for stopping that maximizes the expected value (rewards minus costs) accumulated. The DSKP is analyzed for both the infinite horizon and the finite horizon cases. It is shown that the DSKP has an optimal policy that consists of an easily computed threshold acceptance rule and an optimal stopping rule. A number of monotonicity and convexity properties are studied. This problem is motivated by the issues facing a manager of an LTL transportation operation regarding the acceptance of loads and the dispatching of a vehicle. It also has applications in many other areas, such as the scheduling of batch processors, the selling of assets, the selection of investment projects, and yield management.
The Impact of Cell Dropping Policies in ATM Nodes
Authors: Liu Zhen , Righter Rhonda
Published: December 2003

We consider policies for deciding which cells will be lost or dropped when losses occur at a finite buffer asynchronous transfer mode (ATM) node. The performance criteria of interest are the delay of transmitted (nonlost) cells, the jitter (or variability in the delay of transmitted cells), and the burstiness of lost cells. We analyze the performance trade-offs for various cell dropping policies. We show that “rear dropping,” in which cells that arrive to a full buffer are lost, stochastically maximizes delay, whereas “front dropping,” in which cells at the front of the buffer are lost, stochastically minimizes delay. On the other hand, rear dropping stochastically minimizes the jitter. We also propose policies that have both stochastically smaller delay and less lost cell burstiness in a stochastic majorization sense than the rear dropping policy.
Capital Budgeting Under Uncertainty—An Integrated Approach Using Contingent Claims Analysis and Integer Programming
Authors: Meier Helga , Christofides Nicos , Salkin Gerry
Published: December 2003

Recently the application of contingent claims analysis and dynamic programming to project evaluation has attracted a lot of attention. These techniques are required, for example, if the value of a project develops stochastically over time and the decision to invest into this project can be postponed. Yet, so far there are no considerations regarding how this perception of projects reflects on a capital budgeting situation. We propose two approaches that integrate these methods with traditional capital budgeting models. A simple capital budgeting model can be formulated as the problem of finding the portfolio of options that has maximal value and fulfils the capital expenditure constraint. However, this model has some shortcomings regarding its applicability in traditional budgeting situations. Therefore, we define an alternative optimisation model that uses scenarios to depict a set of possible future states. The optimal portfolio is then equivalent to a dynamic investment strategy that determines a number of state-dependent optimal portfolios.
The Asymptotic Optimality of the SPT Rule for the Flow Shop Mean Completion Time Problem
Authors: Kaminsky Philip , Simchi-Levi David
Published: December 2003

In the flow shop mean completion time problem, a set of jobs has to be processed on m-machines. Every machine has to process each one of the jobs, and every job has the same routing through the machines. The objective is to determine a sequence of the jobs on the machines so as to minimize the sum of the completion times of all jobs on the final machine. In this paper, we prove the asymptotic optimality of the Shortest Processing Time algorithm for any continuous, independent, and identically distributed job processing times.
Dynamic Scheduling for a Flexible Processing Network
Authors: Nam Ick-Hyun
Published: December 2003

We study flexible processing systems where there are multiple paths for a certain type of customer to follow through the system. This paper analyzes an open processing network model with discretionary routing. The underlying methodology is the heavy traffic approximation, which has been well publicized by many researchers. Allowing priority sequencing in addition to dynamic routing as our control policy, we show that the balanced workload routing rule does not necessarily give us an optimal solution. In general unbalanced workload routing with priority sequencing is shown to give us better performance than a balanced one. Through some simulation results we compare our recommendation with other scheduling policies for a flexible processing network.
Optimal Dynamic Allocation of Treatment and Enforcement in Illicit Drug Control
Authors: Tragler Gernot , Caulkins Jonathan P. , Feichtinger Gustav
Published: December 2003

There has been considerable debate about what share of drug control resources should be allocated to treatment vs. enforcement. Most of the debate has presumed that there is one answer to that question, but it seems plausible that the mix of interventions should vary as the size of the problem changes. We formulate the choice between treatment and enforcement as an optimal control problem and reach the following conclusions. If initiation into drug use is an increasing function of the current number of users and control begins early, then it is optimal to use very large amounts of both enforcement and treatment to cut short the epidemic. Otherwise the optimal policy is not to stop the growth of the epidemic, but rather to moderate it. Initially this should be done primarily with enforcement. Over time, enforcement spending should increase, but not nearly so fast as treatment spending. Hence, treatment should receive a larger share of control resources when a drug problem is mature than when it is first growing. If initiation rates subsequently decline, enforcement's budget share should drop further in the ensuing declining stage of the epidemic.
Optimal Replenishment and Rework with Multiple Unreliable Supply Sources
Authors: Chen Jinfa , Yao David D. , Zheng Shaohui
Published: December 2003

We study a production-inventory system with multiple unreliable supply sources. Through inspection and rework, the system can improve the quality of the units received from the supply sources. There are two interleaved decisions: the replenishment quantities from the sources and the inspection-rework quantities among the units received. We show the optimal solution to the replenishment decision can be efficiently derived from a greedy algorithm, and inspection-rework is optimally applied to a single source identified by the algorithm. Furthermore, in the case of linear cost functions, it is optimal to place orders from two supply sources, i.e., dual sourcing. The results extend to the infinite-horizon case, where an order-up-to policy is optimal. The model also readily adapts to situations in which the supply imperfection takes the form of a reduced delivery quantity (yield loss).
The Analytic Hierarchy Process—An Exposition
Authors: Forman Ernest H. , Gass Saul I.
Published: December 2003

This exposition on the Analytic Hierarchy Process (AHP) has the following objectives: (1) to discuss why AHP is a general methodology for a wide variety of decision and other applications, (2) to present brief descriptions of successful applications of the AHP, and (3) to elaborate on academic discourses relevant to the efficacy and applicability of the AHP vis-a-vis competing methodologies. We discuss the three primary functions of the AHP: structuring complexity, measurement on a ratio scale, and synthesis, as well as the principles and axioms underlying these functions. Two detailed applications are presented in a linked document at http://mdm.gwu.edu/FormanGass.pdf .
Online Searching
Authors: Jaillet Patrick , Stafford Matthew
Published: December 2003

We consider the problem of searching m branches which, with the exception of a common source s, are disjoint (hereafter called concurrent branches). A searcher, starting at s, must find a given “exit” t whose location, unknown to the searcher, is on one of the m branches. The problem is to find a strategy that minimizes the worst-case ratio between the total distance traveled and the length of the shortest path from s to t. Additional information may be available to the searcher before he begins his search.

In addition to finding optimal or near optimal deterministic online algorithms for these problems, this paper addresses the “value” of getting additional information before starting the search.
Computing Moments of the Exit Time Distribution for Markov Processes by Linear Programming
Authors: Helmes Kurt , Röhl Stefan , Stockbridge Richard H.
Published: December 2003

We provide a new approach to the numerical computation of moments of the exit time distribution of Markov processes. The method relies on a linear programming formulation of a process exiting from a bounded domain. The LP formulation characterizes the evolution of the process through the moments of the induced occupation measure and naturally provides upper and lower bounds for the exact values of the moments. The conditions the moments have to satisfy are derived directly from the generator of the Markov process and are not based on some approximation of the process. Excellent software is readily available because the computations involve finite dimensional linear programs.
Improving the Sipp Approach for Staffing Service Systems That Have Cyclic Demands
Authors: Green Linda V. , Kolesar Peter J. , Soares João
Published: December 2003

This paper evaluates the practice of determining staffing requirements in service systems with random cyclic demands by using a series of stationary queueing models. We consider Markovian models with sinusoidal arrival rates and use numerical methods to show that the commonly used “stationary independent period by period” (SIPP) approach to setting staffing requirements is inaccurate for parameter values corresponding to many real situations. Specifically, using the SIPP approach can result in staffing levels that do not meet specified period by period probability of delay targets during a significant fraction of the cycle. We determine the manner in which the various system parameters affect SIPP reliability and identify domains for which SIPP will be accurate. After exploring several alternatives, we propose two simple modifications of SIPP that will produce reliable staffing levels in models whose parameters span a broad range of practical situations. Our conclusions from the sinusoidal model are tested against some empirical data.
Parallel Scheduling of Multiclass M/M/m Queues: Approximate and Heavy-Traffic Optimization of Achievable Performance
Authors: Glazebrook Kevin D. , Niño-Mora José
Published: December 2003

We address the problem of scheduling a multiclass M/M/m queue with Bernoulli feedback on m parallel servers to minimize time-average linear holding costs. We analyze the performance of a heuristic priority-index rule, which extends Klimov's optimal solution to the single-server case: servers select preemptively customers with larger Klimov indices. We present closed-form suboptimality bounds (approximate optimality) for Klimov's rule, which imply that its suboptimality gap is uniformly bounded above with respect to (i) external arrival rates, as long as they stay within system capacity; and (ii) the number of servers. It follows that its relative suboptimality gap vanishes in a heavy-traffic limit, as external arrival rates approach system capacity (heavy-traffic optimality). We obtain simpler expressions for the special no-feedback case, where the heuristic reduces to the classical cμ rule. Our analysis is based on comparing the expected cost of Klimov's rule to the value of a strong linear programming (LP) relaxation of the system's region of achievable performance of mean queue lengths. In order to obtain this relaxation, we derive and exploit a new set of work decomposition laws for the parallel-server system. We further report on the results of a computational study on the quality of the cμ rule for parallel scheduling.
Stock Wars: Inventory Competition in a Two-Echelon Supply Chain with Multiple Retailers
Authors: Cachon Gérard P.
Published: December 2003

This paper studies the competitive and cooperative selection of inventory policies in a two-echelon supply chain with one supplier and N retailers. Stochastic demand is monitored continuously. Retailers incur inventory holding and backorder penalty costs. The supplier incurs holding costs for its inventory and backorder penalty costs for backorders at the retailers. The latter cost reflects the supplier's desire to maintain adequate availability of its product to consumers. Previous research finds the supply chain cost minimizing reorder point policies, the cooperative solution. The competitive solution is a Nash equilibrium, a set of reorder points such that no firm can deviate from the equilibrium and lower its cost. It is shown that Nash equilibria exist and a method is presented to find all of them. In some settings the cooperative solution is a Nash equilibrium; competition does not necessarily lead to supply chain inefficiency. In other settings, competition leads to costs that are substantially higher than optimal. Usually (but not always), the competitive supply chain carries too little inventory. Three cooperation strategies are discussed: change incentives, change equilibrium, and change control. A set of contracts is provided that changes the firms' incentives so that the optimal policy is a Nash equilibrium. An equilibrium change can improve performance but does not guarantee optimal performance. To change control, the firms let the supplier choose all reorder points, a key component in vendor managed inventory. That change leads to optimal supply chain performance.
Performance of Bucket Brigades When Work Is Stochastic
Authors: Bartholdi John J. , Eisenstein Donald D. , Foley Robert D.
Published: December 2003

“Bucket brigades” are a way of sharing work on a flow line that results in the spontaneous emergence of balance and consequent high throughput. All this happens without a work-content model or traditional assembly line balancing technology. Here we show that bucket brigades can be effective even in the presence of variability in the work content. In addition, we report confirmation at the national distribution center of a major chain retailer, which experienced a 34% increase in productivity after the workers began picking orders by bucket brigade.
New Two-Stage and Sequential Procedures for Selecting the Best Simulated System
Authors: Chick Stephen E. , Inoue Koichiro
Published: December 2003

Standard “indifference-zone” procedures that allocate computer resources to infer the best of a finite set of simulated systems are designed with a statistically conservative, least favorable configuration assumption consider the probability of correct selection (but not the opportunity cost) and assume that the cost of simulating each system is the same. Recent Bayesian work considers opportunity cost and shows that an average case analysis may be less conservative but assumes a known output variance, an assumption that typically is violated in simulation. This paper presents new two-stage and sequential selection procedures that integrate attractive features of both lines of research. They are derived assuming that the simulation output is normally distributed with unknown mean and variance that may differ for each system. We permit the reduction of either opportunity cost loss or the probability of incorrect selection and allow for different replication costs for each system. The generality of our formulation comes at the expense of difficulty in obtaining exact closed-form solutions. We therefore derive a bound for the expected loss associated potentially incorrect selections, then asymptotically minimize that bound. Theoretical and empirical results indicate that our approach compares favorably with indifference-zone procedures.