Sample-sort simulated annealing.
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.
Thompson
Dale R
DR
Computer Science and Computer Engineering Department, University of Arkansas, Fayetteville, AR 72701, USA. d.r.thompson@ieee.org
Bilbro
Griff L
GL
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted