An Improved Annealing Algorithm Based on Multi-Agent
Authors
Abstract
Considering \u00a0the \u00a0characteristics \u00a0of Simulated \u00a0Annealing \u00a0Algorithm \u00a0(SAA), \u00a0based \u00a0on \u00a0the \u00a0agents\u2019
perception and retroaction to their surroundings, in this paper a new algorithm called Multi-agent Annealing
Algorithm \u00a0(MAA) \u00a0is \u00a0presented. \u00a0And \u00a0the \u00a0global \u00a0convergence \u00a0of \u00a0MAA \u00a0is \u00a0gotten. \u00a0Finally, \u00a0we \u00a0make \u00a0several
numerical \u00a0experiments \u00a0to \u00a0compare \u00a0MAA \u00a0with \u00a0SAA \u00a0and \u00a0Genetic \u00a0Algorithm \u00a0(GA) \u00a0by \u00a0three \u00a0classical \u00a0test
functions in optimization, which suggest that MAA is superior to GA and SAA.