Xpress Optimization Showcase
Using the Power of Optimization to Build Your Competitive Edge

CONTENTS
Product Sheet
FICO Xpress Optimization Suite ……………………………………………………………………………………………. 4-5

Case Study
Optimization soars at American Airlines ……………………………………………………………………………………… 8-9
Honeywell schedules big profits for its clients with FICO Xpress Optimization Suite ……………………………………10-11
Prime Time: The NFL optimizes its playing schedule …………………………………………………………………… 12-13
Optimization drives $19 million gains at Avis ………………………………………………………………………….. 14-15

White Paper
Solving The Unsolvable …………………………………………………………………………………………………. 18-24© 2011 Fair Isaac Corporation. All rights reserved.

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Product Sheet

page 2Make every decision countTM© 2011 Fair Isaac Corporation. All rights reserved.

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FICO™ Xpress Optimization Suite

Xpress-Kalis is Constraint Programming
software based on the Kalis solver by Artelys. It
specializes in discrete combinatorial problems
as they frequently occur, for instance, inscheduling and planning problems.

decision management tools
FICOTM Xpress Optimization
Suite is the premiermathematical modeling andoptimization software suitein the world, with the best
tools available to aid thedevelopment and deployment
of optimization applications
that solve complex, real-world
challenges.

IVE Development Environment»» The competitive advantageof Xpress
FICO is committed to investing heavily in the
Xpress Optimization Suite to maintain it as
the leading optimization technology, and toproviding friendly, high-quality support.
With FICOTM Xpress Optimization Suite, you
can expect:

The Xpress Optimization Suite
helps organizations solve bigger
problems, design applications fasterand make even better decisions in
virtually any business scenario.

• A state-of-the-art optimization engine
that is robust, reliable and faster thancompeting solutions

Improvements to the IVE development environment in Xpress 7 help users build optimization
applications faster than before and design them to match the way their business works.

F

ICOTM Xpress Optimization Suite is aset of mathematical modeling andoptimization tools used to solve linear, integer,
quadratic and non-linear problems. The Xpress
Optimization Suite includes two sets of tools:
model building and development tools, andsolver engines.

»» Model building anddevelopment tools
Xpress-Mosel is an algebraic modeling andprocedural programming language specificallydesigned to be an easy-to-learn, robust way tointeract with Xpress solver engines. It is a fully
functional compiled programming languagethat lets users formulate and solve problems
using one or several of the Xpress solver
engines, and analyze solutions. Xpress-Mosel
now features N-best solution support, making
it easier to develop optimization solutions
that take advantage of the availability ofpage 4Make every decision countTM

approximation, which has been developed
from techniques used in the process industries
and it is capable of solving large problems
with many thousands of variables.

multiple solutions. It also features multiple
problems within one model file for easier
implementation of more advanced solution
algorithms. Xpress-Mosel models can be
developed within IVE, our visual development
studio for Xpress-Mosel under Windows. IVE is
a complete visual development environmentfor Xpress-Mosel which incorporates a Mosel
program editor, compiler and execution
environment, debugger and profiler. Itfeatures development and deployment
wizards, visualizations of the solve progressand results, and a full drag-and-drop editor for
authorizing XAD GUI interfaces. With IVE and
XAD, developers have the tools for complete
optimization application development, fromthe mathematical representation of the
problem to development of the graphicaluser interface. This complete tool set provides
faster prototyping and deployment alongwith visualization tools for greater insight into
customer problems.

»» Solver engines
Xpress-Optimizer features optimization
algorithms that enable customers to solve
their most difficult business problems. It
solves linear programming (LP) problems,
mixed integer programming (MIP) problems,
quadratic programming (QP) problems
and mixed integer quadratic programming(MIQP) problems. Xpress-Optimizer offers
multi-threaded processing out-of-the box,
exploiting multiple CPU cores to solve clients’
most difficult MIP problems. Xpress-Optimizer
includes Builder Component library (BCL), an
object-oriented API for building, solving andanalyzing problems, and C, C++, VB, .NET andJava API support.

• The premier visual development
environment, IVE, for developing
mathematical models, now featuring an
intuitive drag-and-drop editor for creating
GUIs that seamlessly integrate with themodel for rapid prototyping and deployment• An easy-to-learn, powerful modeling andprogramming language, Xpress-Mosel, now
including support for N-best solutions»» FICO and the Xpress Suite»» About FICOThe Xpress Optimization Suite is embeddedin FICO™ Decision Optimizer, the software
component of FICO Custom Decision
Optimization. Custom Decision Optimization
uses Decision Optimizer software alongwith a precise, data-guided methodology
to solve custom decision problems for our
financial services clients in such areas as credit
line management, pricing and market offer
optimization. These complex decisioning
strategies can incorporate any number ofpredictive models while balancing multiple
business objectives (including competing
objectives from various departments) andresource constraints, even accounting forranges of uncertainty.

FICO combines trusted advice, world-classanalytics and innovative applications to
help businesses make smarter decisions.
Our solutions and technologies for Decision
Management give organizations the power toautomate more decisions, improve the qualityof their decisions and connect decisions acrosstheir business.

FICO works in close partnership with its
clients and partners, enabling them to get thebest possible performance from the Xpress
Optimization Suite. The suite is embedded
in many software products and solutions
as a component, making leading-edge
optimization accessible to a wide range ofclients and applications. Through expertise in
the product and its application, excellent client
support and fast-track product development,
FICO continues to maintain the Xpress
Optimization Suite at the cutting edge.

Clients in 80 countries work with FICO toincrease customer loyalty and profitability,
cut fraud losses, manage credit risk, meet
regulatory and competitive demands andrapidly build market share. For more than 50
years, we have helped thousands of clients
control risk and accelerate business growththrough analytics and decision technology.
Our innovative applications integrate analytics,
optimization, business rules management andother technologies to help businesses makesmarter decisions.
For more information and to request
an evaluation copy of the FICOTM Xpress
Optimization Suite, go to
www.fico.com.

• A partner committed to solving all of yourmost difficult optimization problems

Xpress-SLP is a solver for non-linear
programming (NLP) problems andmixed integer non-linear programming(MINLP) problems. It uses successive linear© 2011 Fair Isaac Corporation. All rights reserved.

page 5Case Study

page 6Make every decision countTM© 2011 Fair Isaac Corporation. All rights reserved.

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Optimization soars at American Airlines
success story: optimization

ClientAmerican Airlines, serving nearly 100 million passengers annually

Challenge 	Increase revenue and reduce costs in a highly competitive, low-marginindustry and difficult economic environment

Solution 	FICOTM Xpress Optimization Suite
Results 	Optimized processes that lead to increased revenue, reduced costs andimproved customer service“The difference between sellinga couple of seats or not can be
the difference between being
profitable or losing money ona flight.”—Armando Silva,
managing director of operations
research, American Airlines

For the average airline passenger, a successful
flight means getting from point A to point B
safely and on time. But for the people whowork behind the scenes at American Airlines
and American Eagle, success also depends
on a long and complex list of other factors—scheduling flights, juggling connections,working around bad weather and assigningcrew for nearly 4,000 flights a day.
Add a lagging economy, and it becomes clear:
Running a successful airline is no small feat.
“In today’s economic environment, andparticularly in the airline industry where
margins are very small, maximizing revenue
and reducing cost is a big deal,” says Armando
Silva, managing director of operations researchat American Airlines. “Throughout our history,
but particularly in these tough economic
times, this is the challenge we’ve faced: How
do we take it an extra step? How can we
continue to improve processes and run a morecost-effective, efficient and safe operation?”
Consider that the company strives to provide a
positive experience to 100 million passengers
each year, and the sheer scale of its challenges
becomes mind-boggling. American Airlines
continually works to optimize its operations
in a way that can minimize cost and maximize
revenue, while maintaining the highest levelsof safety and providing quality service to its
passengers. The company has worked toward

page 8Make every decision countTM

these goals with optimization tools for many
years, but the operations research teamwanted to push the bar even higher.

Optimization tackles businesscritical challenges
The airline industry is intensely competitive.
Newer airlines, started in the last decade or
two, have considerably lower operational costs
than legacy companies such as American
Airlines. Fuel prices can spike unpredictably,
making profitability on individual flights achallenge. Such razor-thin margins require
American Airlines to build efficiency into every
part of its operations.
“The difference between selling a couple ofseats or not can be the difference between
being profitable or losing money on a flight,”
Silva says. “In a business with challenges thatare as complex and large as ours, you haveto rely on optimization.” And that kind of
optimization, Silva says, is “something you can’t
do by hand or with a simple tool.”With the help of FICO, American went throughan extensive testing and validation processof Xpress. Results were good and runtimes
were fast.
“That’s a make-it-or-break-it result,” Silva saysof Xpress’s impressive runtimes. “A programthat takes 25 hours to run something is
not that useful.” Based on these results,
American decided to implement Xpress at its
headquarters in Fort Worth, Texas.

Solving problems with
innovation and speed
Today, Xpress touches many important partsof American’s operational decisions, fromlong-term planning to last-minute reroutingof passengers.
First, American Airlines’ operations researchteam works in conjunction with the business
units to develop answers to the businessissues they are trying to solve. Next, theoperations research and decision support
group develops the algorithms, processes
and methodologies for how to solve these
problems. Xpress helps them do this bynarrowing down and choosing the best
possible answers–a critical capability when
the options are virtually innumerable andcomparing them is difficult. They thenpartner with other groups in IT Services to
put into production and run the Xpress-based
systems on a daily or weekly basis—whateverfrequency is required.
Optimization techniques are widely usedat American Airlines For example, when acustomer visits AA.com and purchases aticket, the revenue management group must

reoptimize to determine pricing andavailability for the remaining seats. Whena snowstorm hits Chicago, the system
operations control, reservations and revenue
management groups must reoptimize todetermine how, where and when to reroutedisrupted customers. When an airplane’s
maintenance parts are waiting in Dallas,
Chicago or any other city American serves,the maintenance and engineering andsystem operations control groups must
reoptimize to get the plane to the same city
as its scheduled maintenance. Many of thesefunctions now rely on applications that use
Xpress to perform the required optimization.
Silva says Xpress has expanded his team’s
ability to innovate and apply optimization to
improve business decisions and build moreproductive systems.
“My team is more productive because they
have more access to these kinds of tools, Silva
says. “They’re less constrained by what they
can use to solve their problems. It was a hit in
my group, that’s for sure, when we signed theagreement with FICO.”

Better optimization leads toimproved customer service
At American Airlines many groups benefit
from Xpress-powered applications, suchas operations control, scheduling andmaintenance and engineering, to name afew. These groups benefit from Xpress andmake critical business decisions based ondata generated by Xpress applications.
These decisions ultimately affect customers,
making improved customer service a valuable
result of the decision management tool.

“For example, when we have a disruption,
we do a better job of getting people totheir destination,” Silva says. “That is clearly
improved customer service.”

Optimization spreads
throughout the enterprise
When American Airlines selected Xpress
Optimization Suite, one deciding factor
was the ability to sign an enterprise-wideagreement. That means the OR team candeploy optimization in the face of morechallenges throughout the company.
“Cost was limiting the number of optimization
applications we were able to use,” Silva says.
“Now, with an enterprise Xpress license, we’re
expanding our use of optimization engines
into other areas. We’re less concerned about
monitoring the use of these tools. With thecost savings we have the freedom to use
technology where we need it.”
Looking forward, Silva says he and his teamwill continue to scour the enterprise for ways
to help the business run more smoothly,
better serve its millions of customers andultimately maximize the company’s revenue
and profitability.
“The Xpress Optimization Suite agreementwith FICO, for us, has been an enabler to do
more of these things,” Silva says. “Looking
forward, we will continue to see where we canuse it. We know for a fact there’s a lot more to
be done out there.”

American Airlines turned to the FICOTM Xpress
Optimization Suite. Xpress is designed to helporganizations solve large-scale challenges, andfor American Airlines, this includes making
critical resource allocation, asset management
and scheduling decisions. The technology
includes a set of advanced tools for users todevelop their own optimization models.

© 2011 Fair Isaac Corporation. All rights reserved.

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Honeywell schedules big profits for its clientswith FICO Xpress Optimization Suite
success story: optimization

ClientHoneywell Process Solutions,a division of Honeywell International

Challenge 	Finding a partner with world-class optimization software
that’s transparent to the end user

Solution 	FICO™ Xpress Optimization Suite
Results 	A partner committed to innovation; an optimization

software solution for improved scheduling decisions
that can have a multi-million dollar impact for
manufacturers“We’ve had nothing but a great
experience embedding FICO’s
technology. Embedding Xpress
has been a dream; we’ve hadabsolutely zero issues.”—Jeff Kelly
Solutions Architect,
Honeywell Process Solutions

Long before gasoline is pumped into your car it
flows through a highly orchestrated production
process. In order for refineries to manage thisprocess cost-effectively, each element must be
carefully coordinated.

of many thousands of scheduling scenarios.
“Simply put, our customers come to us withthe challenge of making better schedulingdecisions in an automated and repeatablefashion.”One of the keys to success is the production
schedule. Yet, for many oil-refineries and othercompanies in the continuous process industries(oil and gas exploration and processing,petrochemicals, mining, minerals and metals),
the production schedule is created througha surprisingly low-tech approach: Humans
working manually with spreadsheets.

»» FICO technology partnership
key to success“I’m often surprised at the rudimentary
approach to production scheduling many
companies take,” said Jeff Kelly, Solutions
Architect, Honeywell Process Solutions,a division of Honeywell International.
“Manual scheduling may work, but it’s slow,
inefficient and error prone when compared to
optimization software.”A relatively new technology to the continuous
process industries, optimization software
generates better production schedules,
enabling companies in continuous processindustries to dramatically improve production
efficiency and quality. Unlike manualscheduling, which is restricted by the analytic
limitations of the human brain, optimization
software uses mathematical algorithms toquickly analyze hundreds of variables todetermine the best schedule solution out

page 10Make every decision countTM

When Mr. Kelly joined Honeywell Process
Solutions his mandate was to build Production
Scheduler, a software solution that thecompany would sell to prospects in thecontinuous process industries.
Rather than build the solution in-house,
Mr. Kelly’s strategy was to find a technology
partner with exceptional optimization
technology. He found that in FICO, a pioneer
and industry leader in decision management
and optimization software.

build Production Scheduler without Xpress,
and we would not have had the sales we’ve
had without Xpress,” comments Mr. Kelly.

»» Optimization software 		enables faster, better 		business decisions
With powerful optimization software,
Production Scheduler solves industrial-scale
logistics problems and can help companies
achieve quantifiable improvements in
manufacturing efficiency and quality.
It does this by modeling the complexity ofa manufacturing process, factoring in thehundreds of manufacturing constraints, anddetermining the best possible schedulingsolution. Production Scheduler’s optimization
software provides the decision-making speed
and accuracy to capture market opportunities
that a manual scheduling approach would
never be able to capitalize on. The solution
is designed to handle the full range ofscheduling and blending activities, including:• Crude-oil marine and pipeline scheduling• Refinery crude-oil scheduling• Crude-oil blend optimization• Process unit scheduling• Blend scheduling and optimization• Product distribution to terminals
The economic impact of scheduling
optimization is significant. For example, in
crude-oil blending for a typical oil refinery,
the ability to improve inventory and capacity
schedules can result in $0.078 profit per barrel
each day. While 8 cents appears to be a small
financial impact for an oil barrel per day, thedownstream affect of scheduling demanddriven production for 100,000 barrels equates
to an annual profit increase of $2,850,000.

“Because the Xpress Optimization Suite
can quickly model large-scale, complex
problems, users of Production Scheduler
can make more accurate business decisions
and update to what’s happening in the plantand market more frequently,” says Mr. Kelly.
This reduces risk and uncertainty because
it allows companies to factor the mostcurrent information into their plans. “With
automated and optimized decisions you
can update to market conditions faster thanyour competitors can, which enables you
to capture market opportunities faster thananyone else.”»» Powerful technology that’seasy to use
Despite the power of the Xpress optimization
software, it’s surprisingly user-friendly. A
chemical engineer by trade, Mr. Kelly has noformal computer programming training. Yet
he had no difficulty building the optimization
models that Honeywell’s customers would
use to solve their production problems.
“Xpress is very easy to use, even for people
with little or no computer programming
experience,” says Mr. Kelly. “It’s easy to build
models for all kinds of problems that integrate
well with the software solvers that create theschedule solutions.”
Commenting on Honeywell’s decision toembed the FICOTM Xpress Optimization Suite,
Mr. Kelly has very positive things to say.
“We’ve had nothing but a great experienceembedding FICO’s technology. Embedding
Xpress has been a dream; we’ve hadabsolutely zero issues.”»» Optimization software asa strategic asset
Seeing firsthand how much faster and moreaccurately Honeywell’s customers can solve
problems with Production Scheduler, Mr. Kelly
sees optimization technology as a strategic
asset that every continuous process
manufacturer should use. This is especiallytrue for North American companies, as manyof their competitors in Asia and India are
aggressively embracing new technology
such as optimization software. “What we aredoing for our clients, if you were to draw theiroperating line when making all decisions
manually, we are using that operating line to
make them more competitive and profitablewith automated scheduling optimization.”
Mr. Kelly notes that some companies viewoptimization software as a risk, questioning
whether the time and effort to build models
will yield actual performance gains. “People
may ask, is this optimizer going to be fastenough? Am I going to spend a lot of timeand resources building a model and not haveit perform? Well, that’s not the case anymore.
Xpress has proven to work for large scale,mission critical optimization challenges forour clients.” Mr. Kelly sees no risk using the
FICO Xpress Optimization Suite. “There’s
no question in my mind that companies
using either Production Scheduler or the
Xpress Optimization Suite independently
will improve their manufacturing production
throughput and quality.”
Mr. Kelly is also pleased with FICO’scommitment to innovation. “The incremental
innovation FICO has added to Xpress has
been excellent. The company is continuallyadding new features and enhancements thatwe’ve benefited from.”“Building our own optimization-based solution
wouldn’t get us the world-class performance
we wanted,” said Mr. Kelly. “Instead, we chose
the FICO Xpress Optimization Suite, a powerful
optimization technology that offered all thealgorithms and computing performance todo the thinking for you, to do all the great
searching to find better solutions to complex
decisions.”
Honeywell has sold over 30 copies of Production
Scheduler worldwide in the continuous processindustries. “We would not have been able to© 2011 Fair Isaac Corporation. All rights reserved.

page 11

Prime Time:
The NFL optimizes its playing schedule
success story: optimization

ClientThe National Football League (NFL)

Challenge 	Develop a game schedule that maximizes television ratings andaccommodates the teams and their fans.

Solution 	FICOTM Xpress Optimization Suite
Results 	The NFL can address stadium availability issues, minimize thecompetitive impact of travel, and deliver television schedules that allow
the most fans to watch the biggest games.

»» CHALLENGE“We can solve problems now
that we couldn’t dream ofsolving five years ago. The NFLcontinues to ask for more andmore complicated models, andwith FICO optimization, we areable to deliver.”— Rick Stone,
President of Optimal
Planning Solutions

A delicate balancing act takes place behindthe scenes of every American football gamebroadcast at prime time. The NFL’s 32 teams
play 16 games over 17 weeks at different
stadiums across the country. And for every
game that’s played, television exposure is the
key to business success.
Countless factors must be taken into accountto arrive at an optimal playing schedule:
stadium availability, travel time, days between
games, television placement and more. The
challenge: How to balance the needs of
network partners, the teams and their fans sothat the competition is fair and the league turns
a healthy profit?
“It’s a mathematical problem that could run fora thousand years,” says Rick Stone, Presidentof Optimal Planning Solutions, a consultancy
that helps professional sports leagues createplaying schedules. “Only the most powerful
optimization tool can generate a quality
playing schedule for a sports league like theNFL.”A decade ago, the NFL began to replace its
manual scheduling process with one that
relies on computer software to determine thebest combination of games for the season.
Because of the time-intense process, however,it created no more than a dozen schedules

page 12Make every decision countTM

each year before selecting the official one.
In 2004, the league wanted to improve itsscheduling process by creating and evaluating
as many scenarios as possible, and now
routinely completes and analyzes thousands ofcandidates before finalizing the schedule.
Speed and accuracy were deciding factors inthe search for an optimization tool. In order
to find the best schedule for the season’s 256
games, the tool would have to consider 7,000
game options, while accounting for some
20,000 variables and 50,000 constraints. Above
all, the schedule needed to maximize the value
to the NFL’s television partners while being fair
to its teams and their fans.

“Scheduling the NFL season is an extremely
difficult task and we need the most powerful
optimization software that’s available,”says Stone. “FICOTM Xpress Optimization
Suite outperforms other optimization tools,
including CPLEX, for our sports-schedulingchallenges.”»» SOLUTION
To meet the rigorous scheduling demands, theNFL and Optimal Planning Solutions turned to
the Xpress Optimization Suite software for a
new level of analytic precision and power. The
tool’s ability to solve mixed-integer linear andquadratic programming problems at industryleading speeds, combined with the company’s
track record for top-notch service, persuaded
the NFL to make the switch.
The NFL takes advantage of parallel
implementations for even faster results.
Working across eight CPUs simultaneously,
Xpress system can produce an NFL schedulein 24 hours, which allows the league tochoose the best among thousands of possible
schedules over the course of a two-monthplanning effort.

“Xpress allows us to evaluate infinitely morescheduling options than were possible with amanual process,” says Michael North, Directorof Broadcast Planning and Scheduling for theNFL. “And this capability has improved thequality of our schedules significantly.”
FICO’s optimization software not only
meets the NFL’s scheduling needs today,
but it also has proven that it can keep up
with the increasing complexity each new
football season brings, as the league adds
new variables and constraints. The adventof Thursday games, for example, added a
new set of requirements to the schedule,
as have changing travel and game-spacing
requirements.

»» RESULTS

FICO’s optimization also has enabled the NFL toimprove the way it creates television packages.
In the past, some television placements were
determined only after the schedule wasset, but with FICO’s software the NFL is able
to create the schedule and corresponding
television packages at the same time.
Faster, more thorough and accurate schedules
have translated into higher revenues for theNFL, as the league’s television, sponsorship andlicensing revenue has grown substantially inthe last five years.
“We can solve problems now that we couldn’t
dream of solving five years ago,” says Stone.
“The NFL continues to ask for more andmore complicated models, and with FICO
optimization, we are able to deliver.”A decade ago, it took half a dozen people
sitting in a room 14 hours a day for threemonths to come up with a satisfactoryschedule—the quality of which could only
be evaluated after the football season had
come to a close. Today, the same process
can be accomplished in much less time, withan outcome that accounts for many more

“Xpress outperforms other optimization tools, including CPLEX, for our
sports-scheduling challenges.”— Rick Stone, President of Optimal Planning Solutions
variables and constraints than ever before.

“The NFL scheduling model involves countlessconstraints that must be satisfied to ensure thateach team is being treated fairly, including thenumber of consecutive home or road games,
travel schedules and the number of days off
between games,” says Stone.
A number of internationally known technology
companies bid on the opportunity to help the
NFL solve its scheduling challenge, but few
were able to deliver a workable solution due
to the complexity of the problem. Optimal
Planning Solutions selected FICO from amongleading providers of optimization software inpart because of superior service and software
performance.

© 2011 Fair Isaac Corporation. All rights reserved.

page 13

Optimization drives $19 million gains at Avis
success story: optimization

ClientAvis Europe, a leading car rental company in Europe, Africa, the 		
Middle East and Asia
Challenge 	Maximize the use of every automobile in the company fleet
Solution

FICO Xpress Optimization Suite
TM

Results 	Two-point increase in fleet utilization, translating into an economic
impact of $19 million.

“Because of Xpress, the utilizationof our fleet has gone up by one
or two percentage points. This isa big, big deal for a car rental
company.”— Jens Utech, director of backofficeand station systems, Avis Europe

In the rental car market, success can bemeasured by a simple calculation: The numberof days a car is rented divided by the numberof days the company owns that car. And Avis
Europe is continually striving to achieve that
perfect number.
“It’s straight supply-and-demand forecasting;taking fleet information and working out whichcustomers to sell to and how to best distributeour cars,” says Jens Utech, Avis Europe’s directorof backoffice and station systems. “But getting itright is a complex business process that involves
many variables.”Each year, Avis Europe serves more than 8
million customers at more than 3,800 locations
via the Avis and Budget Brands. It’s Europe’s
No. 2 car-rental agency, controlling 17.7% of the€8.81 billion market in 2007, which comprised 1.2
million vehicles and 44 million rentals.
Avis Europe is perpetually seeking the ideal
car-distribution formula—one that maximizes
profit and sets pricing appropriate for demand.
Previous methods had relied on managers’
intuition and produced satisfactory results, but
Utech and Avis Europe’s board felt that more
could be done.

page 14Make every decision countTM»» From “no forecast andno sophistication” tooptimization accuracy
For many years, Avis Europe’s methodology wasto ask fleet managers and station managers to
examine the reservation system, using routinesthat had been in place for years, and use that
information to predict future demand.
“Every Friday at 7 a.m., one transporter of cars
would go from London Heathrow to Mayfair,
due to demand in downtown London on
weekends,” says Utech. “That’s what we always
did—but there was no way to evaluate if we
could do better.”“In both dimensions, FICOTM Xpress
Optimization Suite was superior to ILOG,”
says Utech, whose company faces a daily
overnight cycle to optimize short-termplanning strategy. “In the fixed-time scenario
the results were much better, and even when
we ran the longer-runtime the results were still
better. Xpress is simply a superior product.”»» A fast rollout yields
impressive results
Using Xpress Optimization Suite, Avis Europe
was able to roll out an initial pilot program in
only a few weeks. Within the year, a new datadriven forecasting system was deployed. At its
heart was the systems-based forecasts whichwere fed into Xpress. The program then createdprecise recommendations for fleet distribution
and utilization.
“It tells us, for example: On Friday morning,
bring only four cars from Heathrow to Mayfair,and bring another four from Stansted Airport,”says Utech.
This kind of precise fleet management is justone of the program’s benefits. Another is its
suggestions for sales restrictions based onrental duration and locations for pick-up andcare return. These strategies ensure that thehighest possible percentage of Avis’ cars go to
its most profitable customers.

“To boost profitability, it could tell us not to
accept any rental reservations made for lessthan three days during specific time periods—
Christmas, for example,” says Utech. And
though Avis has not yet implemented pricingspecific optimization, its fleet-use forecasts leaddirectly to clues for appropriate pricing. “It willtell us that in a special-event situation, we will
run out of cars, so it will prompt us to consider
raising prices beforehand,” says Utech.

»» Decisive recommendations,demonstrable improvement
Avis Europe has implemented the program
across every key market on the continent.
Utech estimates that the program has
accounted for a two-point increase in thecompany’s fleet utilization, which correlates toa $19 million increase in incremental analyzed
benefits. “This,” he says, “is a big, big deal.”
Additional benefits include smoother businessprocesses in the areas of pricing and car
distribution. Transparency in decision making
has also increased with the Xpress reportson the number of reservations at stake forevery decision.
Utech feels that Avis Europe’s customer base isalso experiencing a more subtle benefit:“Even though we haven’t made changes toour customer interface, we’re now in a better
position to put the right car in the right place
for the right customer.”“In the fixed-time scenario theresults were much better, and evenwhen we ran the longer-runtime
the results were still better. Xpress is
simply a superior product.”— Jens Utech,
director of backoffice and station systems,
Avis Europe

The overall success of the project is leading thecompany to implement additional automation
with Xpress and begin fleet-planning
optimization for car-purchasing cycles.
Through it all, says Utech, the service Avis
Europe has received from FICO has been
exemplary, with responses to specificchallenges often coming in less than an hour
and actual code patches arriving in less than
two weeks.
“There’s a strong desire to help, to listen to our
problems and to solve them constructively,”says Utech. “FICO is clearly a better proactive
partner than just about anyone else I can thinkof in the industry.”

Pricing analysts would comb through the samedata with “no forecast and no sophistication,”says Utech, in order to come up with theirestimation for appropriate rental fees.
It wasn’t difficult to see that margins could be
increased through more accurate measurements
and decision making so Avis decided toinvestigate optimization software as a means
to more accurately forecast and increase rental
utilization. Utech helped narrow Avis Europe’s
choices, running head-to-head proof-of-concept
tests between the industry’s two top programs,
FICO Xpress Optimization Suite and ILOG’s
CPLEX, with benchmarks recorded both forlong-runtime solutions as well as those derived
from truncated optimizations.

© 2011 Fair Isaac Corporation. All rights reserved.

page 15

White Paper

page 16Make every decision countTM© 2011 Fair Isaac Corporation. All rights reserved.

page 17

Solving the Unsolvable

Solving the Unsolvable

white paper
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aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper suscipit
lobortis nisl ut aliquip ex ea commodo consequat. Duis autem vel eum iriure dolor in hendreritin vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros etaccumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te
feugait nulla facilisi.

Solving the Unsolvable

Conquering gigantic optimization problems withFICO™ Xpress Optimization
Suite
Heading 2 Example

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aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper suscipit
lobortis nisl ut aliquip ex ea commodo consequat.

January 2011
As problems grow incomplexity, advanced solver
engines are needed that cantackle large-scale optimization
problems. Organizations thatsolve problems efficiently
at all levels of complexity
have a unique competitive
advantage.

Historically, 16- and 32-bit architectures imposed strict limitations on the size of the problem to be
crunched without decomposition. Optimization problems that had 1 million variables and 1 million
Optimization?
constraints were on the periphery of solvable sizes. Introduction of 64-bit architectures expanded
the spectrum of problem sizes and has made it possible to dramatically increase the size of solvableproblems. However, on one hand, some super-large-scale problems are still beyond the hardware
capability, and on the other hand, the solver performance decays non-linearly with the growth of the
problem size. Therefore, large-scale optimization introduces an addedlevel of complexity that requires creativity to ensure a solution to the
FIGURE 1: FICO™ Xpress cuts solution times dramaticallyproblem can actually be derived within the acceptable time limit.

Xpress-Optimizer performance (LP)
300,000
Total Time

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dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent
luptatumzzril delenit augue duis dolore te feugait nulla facilisi.
Summary

250,000»»

Solving 3large,
complex optimization problems can be a daunting task. Conquering
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Examplethemeffectively,
however,canbe thedifference
success
andplacerat
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efficiently
managefloor space,energyaliquamcompanies
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scheduling, marketers can effectively target the right audience with the right offers,
planners
can generate equitable staff schedules, and transport enterprises• personnel
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praesent
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200,000
SECONDS

Goes Here»» What Is Large-Scale

50,0000magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorperreasons,
suscipit lobortis
ut aliquip
excomputationalea commodo consequat.
For these
simply nisl
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thehorsepower is often notenough. As one of the ways to address the scalability issue, next-generation solverNamliber temporcumforsolutanobis
optionproblems
congue nihil
imperdietquod mazimenginesmust lookways
to eleifend
decompose
intosmaller,doming
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placerat facer possim assum. Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diamcomponents. Doing so will allow even the most complex problems to be solved sononummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim adthat keytactical,strategic
andtation
operational
decisionsstill nisl
be ut
made
with
confidence.
minim
veniam,quis nostrud
exerciullamcorper
suscipitcan
lobortisaliquip
ex eacommodoOrganizations that solve problems efficiently at all levels of complexity have a uniqueconsequat.

competitive advantage.

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dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent
luptatum zzril delenit augue duis dolore te feugait nulla facilisi. Lorem ipsum dolor sit amet,consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna
aliquam erat volutpat. Consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut
laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation
ullamcorper suscipit lobortis nisl ut aliquip ex ea commodo consequat.

© 2011 Fair Isaac Corporation. All rights reserved.

page 18

2003B

2004B

2005B

2006B

2007B

2008A

7.0

7.1

RELEASE

Effect of parallelization
300,000
1 threada timelymanner.
improvements
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100,000

To make this process easier, feature-rich solver engines such as FICO™
Xpress Optimizer have been developed to help streamline the task ofcreating and deploying models for optimization problems.
Leveraging a product like Xpress Optimizer, companies can quickly
model and
implement complex decision making processes across the organization.
Increasingly, however, problems are growing in both complexity
and size, so traditional solver engines will no longer suffice. Withlarge-scale optimization, while performance still remains a key
concern, new methods must be introduced to enable solving of
problems that cannot otherwise be solved. To this end, the FICO
Xpress Optimization Suite has introduced new capabilities thatmake large-scale optimization problems more manageable andhelp turn the unsolvable into solvable. The key element in making
this happen is decomposition.

200,000
150,000
100,000
50,0000Modeling optimization problems is usually an intellectuallychallenging exercise. Depending on the problem being solved andthe number of constraints that need to be considered, the process
for creating an adequate model can take a considerable amount oftime without the right set of tools. The situation becomes further
complicated once a valid model is developed. You are then facedwith deciding how to integrate the optimization execution softwarethat utilizes the designed model with a computer application or asuite of products.

4 thread

250,000

SECONDS»» Heading 1 Title

Internal
deterministic

Internal
opportunistic

Coral
deterministic

Coralopportunistic

Figure 1 shows improved performance for linear programming across releases andgreater speeds through parallelization.

Decomposition is simply the process of breaking large optimization
problems into smaller, more manageable sub-problems and solving
them either sequentially or in parallel. There are two well-known
methods to decomposition, namely Benders, a row generation
approach, and Dantzig-Wolfe, a column generation approach.

The solvers and modeling tools of FICO Xpress Optimization Suite support the implementation of
decomposition approaches in various ways. Most importantly, the unique features of Xpress-Mosel,
the modeling language in the Xpress Optimization Suite, make it a particularly suitable platform for

Decomposition is the process of breaking large optimization problems into
smaller, more manageable sub-problems and solving them either sequentiallyor in parallel.

© 2011 Fair Isaac Corporation. All rights reserved.

page 19

Solving the Unsolvable

Solving the Unsolvable»» Decomposition with
Xpress-Mosel

Mosel model
uses ’mmxprs’
uses ’mmxslp’

Mosel instance
Mosel model
shareddata

Problem
Problem

Problemstart
eventsLocal instance
Master model

Problem»» Case Study—

Retail Space Planning

SubmodelProblemRemote instancestart

eventsSubmodelProblem

Challenge:

Xpress-Mosel is designed with an open, modular architecture. Solvers are modules that are loaded into amodel as needed. The Xpress suite comes with a comprehensive set of optimization solvers from which you
can choose the one that is best suited for your problem type, or you can use several solvers in combination
within a single model. Other modules—for example, providing data interfaces or graphics—are also available,
and users can even write their own modules to enhance the Mosel language according to their needs.

Retail space planning requires the solution of relatively large Mixed Integer Programs (MIP), very
combinatorial in nature, for which the current cutting-edge MIP technology would not find a solutionof good quality, even if the solver is left to run for a very long time. Feasibility pump in conjunction
with local-search heuristics and other classes of heuristics implemented in Xpress-Optimizer are key
techniques of specific broader meta-heuristics designed for retail space optimization. In this case,
it is desirable to have Xpress heuristics that can be executed very quickly and to have a modelingenvironment that gives the user easy and efficient ways to handle multiple large or small models/
MIPs in a sequential or parallel fashion.

Multi-Problem

Solution:With Xpress-Mosel, multiple optimization problems can be defined within a single optimization model,
making the process of handling large-scale optimization problems much easier. At any point a single problem
is active, it is possible to switch back and forth between various other problems, allowing for the retrieval ofsolution information across problem components. Problems can share data, make use of common decisionvariables and easily copy constraints from one problem to another or duplicate a problem altogether.

The core MIP models for space planning are very large and combinatorial in nature. Xpress-Mosel
has been a key choice in the implementation of space optimization for a top US retailer, as it gives
efficient ways to handle multiple models
and fast interfaces between them (e.g.,shared memory). As an example, Mosel canhave sub-models running meta-heuristics
in parallel, while the Xpress MIP solver
attempts to close the optimality gap forthe core model, within the allowed time.
As soon as a meta-heuristic finds a better
solution (which is frequent in this type of
application) then the solution is submitted
to the master model that is solving the coremodel. Mosel also proved to be a good
choice with regard to development time, as
the analysts/developers could focus moreon the mathematical programming aspects
and not as much on how to implement
complex decompositions, interfaces andsynchronization mechanisms to handle
multiple models and solvers in the same
project.

FIGURE 2: RETAIL SPACE OPTIMIZATION

Multi-Model

Mosel instance
Master model

Problem solving approaches that involve parallel execution of (sub)models can only be implemented
as multiple models, whereas sequential solving can be formulated either way. For sequential
algorithms, the developer may choose between the two design options. For more detail on thesetechniques, refer to the whitepaper “Multiple models and parallel solving with Mosel”, located on
http://optimization.fico.com.

Multi-Solver

Mosel instance

Problemthe development of decomposition.
Xpress-Mosel is a high-level modeling language combined with standard functionality of
programming languages allowing for the implementation of models and solution algorithms in asingle environment. Through its open, modular architecture, extensions to the language can be madewithout any need for modifications to the core system. The platform-independent compiled models(BIM) are portable across all platforms supported by Xpress and protect your intellectual property
on deployment. Various library interfaces are available for embedding models into applications (C,Java, C#, VB). Model development and analysis is supported by the visual development environment
Xpress-IVE and a set of tools (debugger, profiler).

Xpress-Mosel also allows multiple optimization problems to be implemented as separate model (files). Thisapproach is most suitable if the optimization process should be spread along several threads and executedin parallel. Xpress-Mosel’s unique implementation characteristics make parallel and multithreaded
optimization easily accessible. Readily available communication mechanisms include synchronizationof concurrent models based on event queues and data exchange through shared memory.

Multi-NodeRelease 7.1 of Xpress extends Mosel’s capacities for handling multiple models to distributed computing using
several Mosel instances (running locally or on remote nodes connected through a network). This facility opens
new perspectives for the implementation of decomposition approaches, using all the computing power
available in your local network. Moving from a multi-model application on a single instance to a multi-nodeapplication only requires few changes in a model, largely due to the concept of I/O drivers—prefixes to the filename that indicate how to access a given file (remotely, in memory, compressed, etc.).

Benefit:
Schemes of decomposition and concurrent solving that can be implemented with
Xpress-Mosel include:• Simple parallel runs (different data instances; different algorithm configurations).
• Decomposition approaches (Benders; Dantzig-Wolfe).

Optimized shelf layouts created by Xpress.

• Column generation (loop over top node; branch-and-price).

One of the key performance goals was toachieve a good quality solution, between 1%
and 2% optimality gap, in a very short time,
meaning less than 10 minutes. This could
only be achieved with the decomposition
approach presented above.

• Cut generation (cut-and-branch; branch-and-cut).

© 2011 Fair Isaac Corporation. All rights reserved.

page 20© 2011 Fair Isaac Corporation. All rights reserved.

page 21

Solving the Unsolvable»» Case Study—

Production Scheduling

Solving the Unsolvable»» Case Study—

Challenge:
Production scheduling requires the solution of very large MIPs. A standard way to solve these
problems is to apply chronological decomposition heuristics. As in the previous case, having aneffective modeling and development environment is crucial in first finding the required quality
solutions and then being able to deliver the model in time for deployment.

Challenge:

Online Advertising

Online advertising allocation and pricing models are frequent in today’s Internet market. Highvolumes of bids need to be processed within extremely short time spans.

Solution:

FIGURE 4: MAXIMIZING THE IMPACT OF ONLINE ADVERTISINGThe Xpress MIP solver has been selected forseveral years now by one of the largest software
players in the market. The model requires theefficient solution of very large linear programswith both hard and soft constraints that include
non-linear terms to handle complex cost andinventory functions. The size of this model ismuch superior to the size of the models fromthe previous cases. Therefore, in this case, theinterface adopted is Xpress-BCL 64 bit. BCL isan object oriented library interface to XpressOptimizer. As a library it requires less overhead
in its use than the high-level modeling in
Mosel and it grants direct access to advanced
functionality of the Optimizer library.

FIGURE 3: PRODUCTION SCHEDULING OPTIMIZATION
Revenue

Benefit:

Impressions

Using very efficient implementations of special
ordered sets, Xpress has an effective way toapproximate the non-linear functions and hence
solves the advertising model within the available
time limit.

With efficient implementation of special-ordered sets, Xpress can effectively approximate non-linear
functions.
This Gantt chart generated by Xpress shows optimized production sequence and packaging types.

»» About the FICO Xpress
TM

Solution:
Xpress-Mosel has been used for a large US food/drink manufacturer and has been recently enhanced
to support multi-million, more automated production/packaging lines together with the oldstandard lines. This addition has increased the difficulty of solving the underlying MIPs, which aresolved by applying other specific hierarchical decomposition heuristics implemented efficiently andeffectively using Mosel. Tuning the Xpress MIP solver for these optimization problems proved to bea crucial step in getting the solve times reduced, as well as in getting the required quality solutions.
The Xpress visual environment for Mosel modeling and development, called Xpress-IVE, and theXpress-Tuner have been proficient tools to perform the tuning step.

Optimization Suite

The Xpress optimization suite includes a wide range of fast solvers and modeling interfaces. The
modeling and solving environment of Xpress-Mosel is an easy-to-learn modeling and programming
language that supports your efforts from rapid prototyping to in-depth model development
and tuning. It comes with a visual development environment (Xpress-IVE), that makes it easier for
developers to get new optimization initiatives to market faster. The suite also benefits from the close
link between Xpress-Mosel and the Xpress solvers and is thus the perfect tool for the implementationof decomposition approaches. An alternative modeling interface is the builder component library
Xpress-BCL. This object-oriented library adds advanced modeling functionality to your preferred
programming language (available in Java, C, C++, .Net).

Benefit:
By using this approach we were able to bring down the solve times to approximately five minutes on
average, which fulfilled the customer requirements.

© 2011 Fair Isaac Corporation. All rights reserved.

page 22© 2011 Fair Isaac Corporation. All rights reserved.

page 23

Solving the Unsolvable

Explore the full power of the FICO™ Xpress Optimization Suite
FIGURE 5: FICO™ XPRESS VISUAL DEVELOPMENT ENVIRONMENT
Xpress-IVE model editor

Discover how the rules are changing
http://decisions.fico.com/downloadTrial.html

Xpress-XAD application design

To get the most out of our software, training courses and consultancy ranging from just a few
hours to fully implementing customer specific solutions are offered.

Learn more about Xpress
Xpress website: www.fico.com/xpress
Xpress documentation & whitepapers: http://optimization.fico.com
Searchable on-line examples database: http://examples.xpress.fico.com
Trial download: http://decisions.fico.com/downloadTrial.html© 2011 Fair Isaac Corporation. All rights reserved.

page 24© 2011 Fair Isaac Corporation. All rights reserved.

page 25

Contact

ASIA PACIFIC REGIONAL HEADQUARTERS

GENERAL INFORMATION AND SALES

FICO - Singapore
8 Shenton Way, #40-01,
AXA Tower, Singapore 068811
Tel: +65 6323 9700
Fax: +65 6323 3449
Email: infoasia@fico.com

Tel: +65 6323 9700
Email: infoasia@fico.com

MAIN OFFICES
Australia - Sydney
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19-29 Martin Place
Sydney, NSW 2000, Australia
Tel: +61 2 9238 1930
Fax: +61 2 9614 5670

page 26

PRODUCT SUPPORT
Tel: +65 6323 9737
Email: support@fico.com

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Fax: +81 3 6212 2769

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Make every decision countTM