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A parallel stochastic method for solving linearly constrained concave global minimization problems |
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| Authors: | A T Phillips J B Rosen M Van Vliet |
| Institution: | (1) Computer Science Department, United States Naval Academy, 21402 Annapolis, MD, U.S.A.;(2) Computer Science Department, University of Minnesota, 55455 Minneapolis, MN, U.S.A.;(3) Tinbergen Institute, Erasmus University, Rotterdam, The Netherlands |
| Abstract: | A parallel stochastic algorithm is presented for solving the linearly constrained concave global minimization problem. The algorithm is a multistart method and makes use of a Bayesian stopping rule to identify the global minimum with high probability. Computational results are presented for more than 200 problems on a Cray X-MP EA/464 supercomputer. |
| Keywords: | Constrained global minimization stochastic method multistart technique Bayesian stopping rule parallel computation |
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