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Simulation-Based Decision Making for Complex Systems

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27 May 2009
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Over the last several decades, computer simulationshave been widely utilized to model and analyzecomplex systems at low costs and risks. Althoughsimulation can represent physical systemsrealistically, it is a descriptive tool without thecapability of suggesting better solutions. However,it can be complemented by incorporating optimizationroutines. The most challenging problem is thatlarge-scale simulation models normally take aconsiderable amount of computer time to execute sothat the number of solution evaluations needed bymost optimization algorithms is not feasible within areasonable time frame. This book, therefore, providesa highly efficient evolutionary simulation-baseddecision making procedure which can be applied inreal-time management situations. We have used thisnovel simulation-optimization technique to studyseveral disaster response problems. The methodologiesprovided herein should be useful to professionals andresearchers in the fields of industrial engineeringand operations research. The applications in disasterresponse management should help emergency managersand personnel to gain insights into severalsignificant response problems.

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    Product Details
    ISBN-13
    9783639156201
    Author
    Shengnan Wu
    Publisher
    KS OmniScriptum Publishing
    Published
    27 May 2009
    Format
    Paperback / softback

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    RRP: $88.86
    $87.08
    Ships in 3-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Simulation-Based Decision Making for Complex Systems

    RRP: $88.86
    $87.08

    Description

    Over the last several decades, computer simulationshave been widely utilized to model and analyzecomplex systems at low costs and risks. Althoughsimulation can represent physical systemsrealistically, it is a descriptive tool without thecapability of suggesting better solutions. However,it can be complemented by incorporating optimizationroutines. The most challenging problem is thatlarge-scale simulation models normally take aconsiderable amount of computer time to execute sothat the number of solution evaluations needed bymost optimization algorithms is not feasible within areasonable time frame. This book, therefore, providesa highly efficient evolutionary simulation-baseddecision making procedure which can be applied inreal-time management situations. We have used thisnovel simulation-optimization technique to studyseveral disaster response problems. The methodologiesprovided herein should be useful to professionals andresearchers in the fields of industrial engineeringand operations research. The applications in disasterresponse management should help emergency managersand personnel to gain insights into severalsignificant response problems.

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