OPL (Optimization Programming Language) is a new modeling language for combinatorial optimization that simplifies the formulation and solution of optimization problems. Perhaps the most significant dimension of OPL is the support for constraint programming, including sophisticated search specifications, logical and higher order constraints, and support for scheduling and resource allocation applications. This book, written by the developer of OPL, is a comprehensive introduction to the OPL programming language and its application to problems in linear and integer programming, constraint programming, and scheduling. Readers should be familiar with combinatorial optimization, at least from an application standpoint.

This volume presents a unique combination of modeling and solving real world optimization problems. It is the only book which treats systematically the major modeling languages and systems used to solve mathematical optimization problems, and it also provides a useful overview and orientation of today's modeling languages in mathematical optimization. It demonstrates the strengths and characteristic features of such languages and provides a bridge for researchers, practitioners and students into a new world: solving real optimization problems with the most advances modeling systems.

Optimization problems in practice are diverse and evolve over time, giving rise to - quirements both for ready-to-use optimization software packages and for optimization software libraries, which provide more or less adaptable building blocks for app- cation-specific software systems. In order to apply optimization methods to a new type of problem, corresponding models and algorithms have to be “coded” so that they are accessible to a computer. One way to achieve this step is the use of a mod- ing language. Such modeling systems provide an excellent interface between models and solvers, but only for a limited range of model types (in some cases, for example, linear) due, in part, to limitations imposed by the solvers. Furthermore, while m- eling systems especially for heuristic search are an active research topic, it is still an open question as to whether such an approach may be generally successful. Modeling languages treat the solvers as a “black box” with numerous controls. Due to variations, for example, with respect to the pursued objective or specific problem properties, - dressing real-world problems often requires special purpose methods. Thus, we are faced with the difficulty of efficiently adapting and applying appropriate methods to these problems. Optimization software libraries are intended to make it relatively easy and cost effective to incorporate advanced planning methods in application-specific software systems. A general classification provides a distinction between callable packages, nume- cal libraries, and component libraries.

Today many organizations face challenges when developing a realistic plan or schedule that provides the best possible balance between customer service and revenue goals. Optimization technology has long been used to find the best solutions to complex planning and scheduling problems. A decision-support environment that enables the flexible exploration of all the trade-offs and sensitivities needs to provide the following capabilities: Flexibility to develop and compare realistic planning and scheduling scenarios Quality sensitivity analysis and explanations Collaborative planning and scenario sharing Decision recommendations This IBM® Redbooks® publication introduces you to the IBM ILOG® Optimization Decision Manager (ODM) Enterprise. This decision-support application provides the capabilities you need to take full advantage of optimization technology. Applications built with IBM ILOG ODM Enterprise can help users create, compare, and understand planning or scheduling scenarios. They can also adjust any of the model inputs or goals, and fully understanding the binding constraints, trade-offs, sensitivities, and business options. This book enables business analysts, architects, and administrators to design and use their own operational decision management solution.

This book is meant to help you get started writing mathematical models in a commercial modeling language, IBM ILOG CPLEX Studio 12.4. Learning a modeling language gives you the flexibility to create your own industrial-strength models and helps you understand the field of optimization better.

Audience: Anyone concerned with the science, techniques and ideas of how decisions are made."--BOOK JACKET.

This volume contains the proceedings of the Ninth International Conference on Principles and Practice of Constraint Programming (CP 2003), held in Kinsale, Ireland, from September 29 to October 3, 2003. Detailed information about the CP 2003 conference can be found at the URL http://www.cs.ucc.ie/cp2003/ The CP conferences are held annually and provide an international forum for the latest results on all aspects of constraint programming. Previous CP conferences were held in Cassis (France) in 1995, in Cambridge (USA) in 1996, in Schloss Hagenberg (Austria) in 1997, in Pisa (Italy) in 1998, in Alexandria (USA) in 1999, in Singapore in 2000, in Paphos (Cyprus) in 2001, and in Ithaca (USA) in 2002. Like previous CP conferences, CP 2003 again showed the interdisciplinary nature of computing with constraints, and also its usefulness in many problem domains and applications. Constraint programming, with its solvers, languages, theoretical results, and applications, has become a widely recognized paradigm to model and solve successfully many real-life problems, and to reason about problems in many research areas.