An adaptive simulated annealing algorithm for global optimization over continuous variables

Andrew E.W. Jones*, G. W. Forbes

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)

Abstract

A method is presented for attempting global minimization for a function of continuous variables subject to constraints. The method, called Adaptive Simulated Annealing (ASA), is distinguished by the fact that the fixed temperature schedules and step generation routines that characterize other implementations are here replaced by heuristic-based methods that effectively eliminate the dependence of the algorithm's overall performance on user-specified control parameters. A parallelprocessing version of ASA that gives increased efficiency is presented and applied to two standard problems for illustration and comparison.

Original languageEnglish
Pages (from-to)1-37
Number of pages37
JournalJournal of Global Optimization
Volume6
Issue number1
DOIs
Publication statusPublished - Jan 1995
Externally publishedYes

Keywords

  • Global optimization
  • Monte Carlo optimization
  • simulated annealing

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