Logic has recently become a basic modelling tool alongside mathematics, and the two styles of modelling are beginning to combine. Thus the need for logical inference models, particularly those that involve quantitative methods, is growing. As generated in operations research and computer science, the methods of combinatorial optimization can be powerful tools for understanding and solving logical inference problems which arise in Artificial Intelligence (AI) and other fields.

Unique in that it focuses on formulation and case studies rather than solutions procedures covering applications for pure, generalized and integer networks, equivalent formulations plus successful techniques of network models. Every chapter contains a simple model which is expanded to handle more complicated developments, a synopsis of existing applications, one or more case studies, at least 20 exercises and invaluable references.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.

A complete, self-contained introduction to a powerful and resurging mathematical discipline . Combinatorial Geometry presents and explains with complete proofs some of the most important results and methods of this relatively young mathematical discipline, started by Minkowski, Fejes Toth, Rogers, and Erd s. Nearly half the results presented in this book were discovered over the past twenty years, and most have never before appeared in any monograph. Combinatorial Geometry will be of particular interest to mathematicians, computer scientists, physicists, and materials scientists interested in...

Noted researchers, including George Nemhauser, Richard Larson and Laurence Wolsey, contributed papers to this comprehensive text/reference on present-day theory and algorithms for locational problems where the decisions are of a discrete nature.

Provides an in-depth treatment of the Traveling Salesman problem--the archetypical problem in combinatorial optimization. Each chapter deals with a different aspect of the problem, and has been written by an acknowledged expert in the field. Focusses on the essential ideas in a self-contained manner. Includes exercises and an extensive bibliography.

Annealing is the physical process of heating up a solid until it melts, followed by careful cooling until it cristalyzes in a state corresponding to a perfect lattice. In combinatorial optimization a similar process can be defined and the resulting method is called simulated annealing. A substantial reduction of the computational effort required by the simulated annealing algorithm may be achieved by using computational models that are based on massively parallel execution. An example of such a model is the Boltzmann machine. A Boltzmann machine is thought to consist of a large network of...