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Simulation Optimisation: Approaches, Examples, and Experiences

By Peter Köchel

Abstract

Simulation based optimisation or simulation optimisation is an important field in stochastic optimisation. The present report introduces into that problem area. We distinguish between the non-recursive and recursive approaches of simulation optimisation. For the non-recursive approach we consider three methods, the retrospective, SPO-, and the RS-methods. With the help of a simple inventory problem we discuss the advantages and disadvantages of these methods. As a recursive method we consider in the second part of our report the coupling of simulation with Genetic Algorithms. As an application example we take a complex multi-location inventory model with lateral transshipments. From our experiences with such optimisation problems we finally formulate some principles, which may be relevant in simulation optimisation

Topics: Genetische Algorithmen, Lagerhaltungsmodell, ddc:004, ddc:510, ddc:620, ddc:330, Optimierung, Simulation, Stochastisches System
Publisher: Universitätsbibliothek Chemnitz
Year: 2009
OAI identifier: oai:qucosa.de:bsz:ch1-200900682

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