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Simulated Annealing (SA) is an effective general heuristic method for solving many com-binatorial optimization problems. However, SA has two drowbacks. One is the long computational time of the annealings. The other one is the determination of the appropriate temperature schedule in SA. This paper proposes a new parallel SA model(PSA/AT(GA)) which(More)
— When SA is applied to continuous optimization problems, the design of the neighborhood used in SA becomes important. A lot of experiments are necessary to determine an appropriate neighborhood range in each problem, because the neighborhood range corresponds to the distance in the Euclid space and is decided arbitrarily. We proposed a Multi-point(More)
When applying SA to continuous optimization problems, the appropriate adjustment of the neighborhood ranges becomes necessary to obtain the good performance. In this paper, we propose a Neighborhood Parallel Simulated Annealing (NPSA) for continuous optimization problems, which provides global search using the periodic exchange of different neighborhood(More)
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