A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems ― Nonconvex Optimization and Its Applications
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Sets out a new method for generating tight linear or convex programming relaxations for discrete and continuous nonconvex programming problems, featuring a model that affords a useful representation and structure, further strengthened with an automatic reformulation and constraint generation technique. Offers a unified treatment of discrete and continuous nonconvex programming problems, bridging these two types of nonconvexities with a polynomial representation of discrete constraints, and discusses special applications to discrete and continuous nonconvex programs. Material comprises original work of the authors compiled from several journal publications. No index. Annotation c. by Book News, Inc., Portland, Or.
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