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Buchholz, Peter

Optimization of Stochastic Discrete Event Simulation Models

09261.BuchholzPeter.ExtAbstract.2182.pdf (0.1 MB)


Many systems in logistics can be adequately modeled using stochastic discrete event simulation models. Often these models are used to find a good or optimal configuration of the system. This implies that optimization algorithms have to be coupled with the models. Optimization of stochastic simulation models is a challenging research topic since the approaches should be efficient, reliable and should provide some guarantee to find at least in the limiting case with a runtime going to infinite the optimal solution with a probability converging to 1. The talk gives an overview on the state of the art in simulation optimization. It shows that hybrid algorithms combining global and local optimization methods are currently the best class of optimization approaches in the area and it outlines the need for the development of software tools including available algorithms.

BibTeX - Entry

  author =	{Peter Buchholz},
  title =	{Optimization of Stochastic Discrete Event Simulation Models},
  booktitle =	{Models and Algorithms for Optimization in Logistics},
  year =	{2009},
  editor =	{Cynthia Barnhart and Uwe Clausen and Ulrich Lauther and Rolf H. M{\"o}hring},
  number =	{09261},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{},
  annote =	{Keywords: Stochastic discrete event simulation, optimization, hybrid algorithms}

Keywords: Stochastic discrete event simulation, optimization, hybrid algorithms
Seminar: 09261 - Models and Algorithms for Optimization in Logistics
Issue Date: 2009
Date of publication: 02.10.2009

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