Logic-Based Methods for Optimization

JOHN HOOKER, PhD, is Professor of Operations Research and T. Jerome Holleran Professor of Business Ethics and Social Responsibility at the Graduate School of Industrial Administration, Carnegie Mellon University. Well-known for his work in the operations research/computer science interface, Dr. Hooker has published over 80 articles and coauthored (with Vijay Chandru) Optimization Methods for Logical Inference, also available from Wiley.

• Some Examples. The Logic of Propositions. The Logic of Discrete Variables. The Logic of 0-1 Inequalities. Cardinality Clauses. Classical Boolean Methods. Logic-Based Modeling. Logic-Based Branch and Bound. Constraint Generation. Domain Reduction. Constraint Programming. Continuous Relaxations. Decomposition Methods. Branching Rules. Relaxation Duality. Inference Duality. Search Strategies. Logic-Based Benders Decomposition. Nonserial Dynamic Programming. Discrete Relaxations. References. Index.

"This is a book that should be widely read by graduate students and researchers in both the computer science and optimization communities." (Choice, Vol. 38, No. 7, March 2001)"Goal is to broaden the conceptual foundations of optimization to include logical and constraint based approaches to traditional optimization methods." (American Mathematical Monthly, November 2001)"The author combines a low-key, often conversational presentation with enthusiasm for a synthesis with traditional optimization methods..." (SIAM Review, Vol. 43, No. 4)"The book is for practitioners as well as theorists" (Zentralblatt Math, Vol.974, No.24, 2001)