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    General methodology 3: global search strategies for simulation optimisation

    Magoulas, George and Eldabi, T. and Paul, R.J. (2002) General methodology 3: global search strategies for simulation optimisation. In: Snowdon, J.L. and Charnes, J.M. (eds.) Proceedings of the 34th Winter Simulation Conference: Exploring New Frontiers. IEEE Computational Intelligence Society, pp. 1978-1985. ISBN 0780376145.

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    Abstract

    Simulation optimization is rapidly becoming a mainstream tool for simulation practitioners, as several simulation packages include add-on optimization tools. We are concentrating on an automated optimization approach that is based on adapting model parameters in order to handle uncertainty that arises from stochastic elements of the process under study. We particularly investigate the use of global search methods in this context, as these methods allow the optimization strategy to escape from sub-optimal (i.e., local) solutions and, in that sense, they improve the efficiency of the simulation optimization process. The paper compares several global search methods and demonstrates the successful application of the Particle Swarm Optimizer to simulation modeling optimization and design of a steelworks plant, a representative example of the stochastic and unpredictable behavior of a complex discrete event simulation model.

    Metadata

    Item Type: Book Section
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 29 Jun 2021 13:52
    Last Modified: 29 Jun 2021 13:52
    URI: https://eprints.bbk.ac.uk/id/eprint/44922

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