Bridges the gap between theory and practice in operational research and management science. The first part discusses general principles of model building in mathematical programming, including discussion of commercially available computer programs. The second part comprises twenty practical problems, and the final sections suggest formulations for, and solutions to, these problems. Throughout, the stress is on building and interpreting the models rather than on the details of the algorithms.

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'Such a text - and this is the only one of this type I know of - should be the basis of all instruction in Mathematical Programming.' Journal of the Royal Statistical Society

'An excellent introduction ... for students of business administration and people who want to see the utility of operations research.' European Journal of Operational Research

'It will be appreciated very much by practitioners who already have knowledge in the field of mathematical programming.' Mathematical Programming Society Newsletter Model Building in Mathematical Programming Fourth Edition H. Paul Williams Faculty of Mathematical Studies, University of Southampton, UK

This extensively revised fourth edition of this well-known and much praised book contains a great deal of new material. In particular sections and new problems have been added covering Revenue Management. Hydro Electric Generation, Date Envelopment (efficiency) Analysis, Milk Distribution and Collection and Constraint Programming. The book discusses the general principles of model building in mathematical programming and shows how they can be applied by using simplified but practical problems from widely different contexts. Suggested formulations and solutions are given in the latter part of the book together with computational experience to give the reader a feel for the computation difficulty of solving that particular type of model. Aimed at undergraduates, postgraduates, research students and managers, this book illustrates the scope and limitations of mathematical programming, and shows how it can be applied to real situations. By emphasizing the importance of the building and interpretation of models rather than the solution process, the author attempts to fill a gap left by the many works which concentrate on the algorithmic side of the subject.

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