Evolutionary Selection in Simulation-Based Optimization

  • Authors:

  • Andreas Beham;Monika Kofler;Michael Affenzeller;Stefan Wagner

  • Affiliations:

  • Josef Ressel Centre for heuristic optimization - Heureka! School of Informatics, Communications and Media - Hagenberg, Upper Austria University of Applied Sciences, Hagenberg, Austria A-4232;Josef Ressel Centre for heuristic optimization - Heureka! School of Informatics, Communications and Media - Hagenberg, Upper Austria University of Applied Sciences, Hagenberg, Austria A-4232;Josef Ressel Centre for heuristic optimization - Heureka! School of Informatics, Communications and Media - Hagenberg, Upper Austria University of Applied Sciences, Hagenberg, Austria A-4232;Josef Ressel Centre for heuristic optimization - Heureka! School of Informatics, Communications and Media - Hagenberg, Upper Austria University of Applied Sciences, Hagenberg, Austria A-4232

  • Venue:
  • Computer Aided Systems Theory - EUROCAST 2009
  • Year:
  • 2009

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Abstract

In this work we examine the effect of elitist and non-elitist selection on a supply chain problem. The problem is characterized by an output constraint which in turn separates the search space in a feasible and a non-feasible region. Additionally the simulation output is noisy due to a stochastic demand model. We will show analyze which strategy is able to perform a walk on the boundary between the feasible and infeasible space. Additionally a new selection scheme is introduced based on a statistical test to evaluate the difference between two solutions given a number of noisy quality values. This selection scheme is described and evaluated on the problem situation.