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

  • Authors:

  • Scott L. Rosen;Catherine M. Harmonosky

  • Affiliations:

  • The Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, 310 Leonhard Building, University Park, PA;The Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, 310 Leonhard Building, University Park, PA

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2005

Quantified Score

Hi-index 0.01

Visualization

Abstract

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.