Parallel Branch-and-bound Attraction Based Methods for Global Optimzation
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In this paper a parallel version of an attraction based branch-and-bound method for global optimization is presented. The method has been implemented and tested using a parallel Scali system. Some well known test functions as well as two practical problems were used for the testing. The results show the prospectiveness of dynamic load balancing for the distributed parallelization of the considered algorithm.
KeywordsGlobal optimization parallel branch-and-bound testing of GO algorithms
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