The primary objective underlying the Handbook on Modelling for
Discrete Optimization is to demonstrate and detail the pervasive
nature of Discrete Optimization. While its applications cut across
an incredibly wide range of activities, many of the applications
are only known to specialists. It is the aim of this handbook to
correct this.
It has long been recognized that "modelling" is a critically
important mathematical activity in designing algorithms for solving
these discrete optimization problems. Nevertheless solving the
resultant models is also often far from straightforward. In recent
years it has become possible to solve many large-scale discrete
optimization problems. However, some problems remain a challenge,
even though advances in mathematical methods, hardware, and
software technology have pushed the frontiers forward. This
handbook couples the difficult, critical-thinking aspects of
mathematical modelling with the hot area of discrete optimization.
It will be done in an academic handbook treatment outlining the
state-of-the-art for researchers across the domains of the Computer
Science, Math Programming, Applied Mathematics, Engineering, and
Operations Research. Included in the handbook's treatment are
results from Graph Theory, Logic, Computer Science, and
Combinatorics.
The chapters of this book are divided into two parts: (1) one
dealing with general methods in the modelling of discrete
optimization problems and (2) the other with specific applications.
The first chapter of this volume, written by H. Paul Williams, can
be regarded as a basic introduction of how to model discrete
optimization problems as mixed integer problems, and outlines the
main methods of solving them. In the second part of the book
various real life applications are presented, most of them
formulated as mixed integer linear or nonlinear programming
problems. These applications include network problems, constant
logic problems, many engineering problems, computer design, finance
problems, medical diagnosis and medical treatment problems,
applications of the Genome project, an array of transportation
scheduling problems, and other applications.
Further information including a detailed Table of Contents and
Preface can be found and examined on the Handbook's web page at
http: //www.springer.com/0-387-32941-2.
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