Sample-sort simulated annealing.

Dale R Thompson; Griff L Bilbro

doi:10.1109/tsmcb.2005.843972

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Sample-sort simulated annealing.

Dale R Thompson·Griff L Bilbro

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Abstract

A simulated annealing (SA) algorithm called Sample-Sort that is artificially extended across an array of samplers is proposed. The sequence of temperatures for a serial SA algorithm is replaced with an array of samplers operating at static temperatures and the single stochastic sampler is replaced with a set of samplers. The set of samplers uses a biased generator to sample the same distribution of a serial SA algorithm to maintain the same convergence property. Sample-Sort was compared to SA by applying both to a set of global optimization problems and found to be comparable if the number of iterations per sampler was sufficient. If the evaluation phase dominates the computational requirements, Sample-Sort could take advantage of parallel processing.

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Algorithms Artificial Intelligence Cluster Analysis Information Storage and Retrieval Models, Biological Models, Statistical Numerical Analysis, Computer-Assisted Pattern Recognition, Automated Reproducibility of Results Sample Size Sensitivity and Specificity Signal Processing, Computer-Assisted Evaluation Study Journal Article

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Dale R Thompson, Griff L Bilbro. 2005. Sample-sort simulated annealing.. https://doi.org/10.1109/tsmcb.2005.843972

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