Reformulation-Linearization Techniques for Discrete Optimization Problems

Hanif D. Sherali () and Warren P. Adams
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Hanif D. Sherali: Virginia Polytechnic Institute and State University, Department of Industrial and Systems Engineering
Warren P. Adams: Clemson University, Department of Math Sciences

A chapter in Handbook of Combinatorial Optimization, 1998, pp 479-532 from Springer

Abstract: Abstract Discrete and continuous nonconvex programming problems arise in a host of practical applications in the context of production, location-allocation, distribution, economics and game theory, process design, and engineering design situations. Several recent advances have been made in the development of branch-and-cut algorithms for discrete optimization problems and in polyhedral outer-approximation methods for continuous nonconvex programming problems. At the heart of these approaches is a sequence of linear programming problems that drive the solution process. The success of such algorithms is strongly tied in with the strength or tightness of the linear programming representations employed.

Keywords: Convex Hull; Discrete Optimization; Valid Inequality; Quadratic Assignment Problem; Discrete Optimization Problem (search for similar items in EconPapers)
Date: 1998
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DOI: 10.1007/978-1-4613-0303-9_7

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