An improved simulated annealing simulation optimization method for discrete parameter stochastic systems

Scott L. Rosen, Catherine M. Harmonosky

Research output: Contribution to journalArticle

48 Scopus citations


This paper proposes a new heuristic algorithm for the optimization of a performance measure of a simulation model constrained under a discrete decision space. It is a simulated annealing-based simulation optimization method developed to improve the performance of simulated annealing for discrete variable simulation optimization. This is accomplished by basing portions of the search procedure on inferred statistical knowledge of the system instead of using a strict random search. The proposed method is an asynchronous team-type heuristic that adapts techniques from response surface methodology and simulated annealing. Testing of this method is performed on a detailed simulation model of a semi-conductor manufacturing process consisting of over 40 work-stations with a cost minimization objective. The proposed method is able to obtain superior or equivalent solutions to an established simulated annealing method during each run of the testing experiment.

Original languageEnglish (US)
Pages (from-to)343-358
Number of pages16
JournalComputers and Operations Research
Issue number2
StatePublished - Feb 1 2005


All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research

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