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Computational experience using an edge search algorithm for linear reverse convex programs

โœ Scribed by Stephen E. Jacobsen; Khosrow Moshirvaziri


Publisher
Springer US
Year
1996
Tongue
English
Weight
831 KB
Volume
9
Category
Article
ISSN
0925-5001

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โœฆ Synopsis


This paper presents computational experience with a rather straight forward implementation of an edge search algorithm for obtaining the globally optimal solution for linear programs with an additional reverse convex constraint. The paper's purpose is to provide a collection of problems, with known optimal solutions, and performance information for an edge search implementation so that researchers may have some benchmarks with which to compare new methods for reverse convex programs or concave minimization problems. There appears to be nothing in the literature that provides computational experience with a basic edge search procedure. The edge search implementation uses a depth first strategy. As such, this paper's implementation of the edge search algorithm is a modification of Hillestad's algorithm [ 111. A variety of test problems is generated by using a modification of the method of Sung and Rosen [20], as well as a new method that is presented in this paper. Test problems presented may be obtained at ftp://newton.ee.ucla.edu/nonconvex/pub/.


๐Ÿ“œ SIMILAR VOLUMES


A Parallel Algorithm for Linear Programs
โœ Shih-Mim Liu; G.P. Papavassilopoulos ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 211 KB

A parallel method for globally minimizing a linear program with an additional reverse convex constraint is proposed which combines the outer approximation technique and the cutting plane method. Basically p (โ‰คn) processors are used for a problem with n variables and a globally optimal solution is fo