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Simulation-Based Decision Making for Complex Systems

Simulation-Based Decision Making for Complex Systems in Vernon, BC

Current price: $95.50
Buy Online
Simulation-Based Decision Making for Complex Systems

Coles

Simulation-Based Decision Making for Complex Systems in Vernon, BC

Current price: $95.50
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Size: Paperback

Buy Online
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Over the last several decades, computer simulations have been widely utilized to model and analyze complex systems at low costs and risks. Although simulation can represent physical systems realistically, it is a descriptive tool without the capability of suggesting better solutions. However, it can be complemented by incorporating optimization routines. The most challenging problem is that large-scale simulation models normally take a considerable amount of computer time to execute so that the number of solution evaluations needed by most optimization algorithms is not feasible within a reasonable time frame. This book, therefore, provides a highly efficient evolutionary simulation-based decision making procedure which can be applied in real-time management situations. We have used this novel simulation-optimization technique to study several disaster response problems. The methodologies provided herein should be useful to professionals and researchers in the fields of industrial engineering and operations research. The applications in disaster response management should help emergency managers and personnel to gain insights into several significant response problems.
Over the last several decades, computer simulations have been widely utilized to model and analyze complex systems at low costs and risks. Although simulation can represent physical systems realistically, it is a descriptive tool without the capability of suggesting better solutions. However, it can be complemented by incorporating optimization routines. The most challenging problem is that large-scale simulation models normally take a considerable amount of computer time to execute so that the number of solution evaluations needed by most optimization algorithms is not feasible within a reasonable time frame. This book, therefore, provides a highly efficient evolutionary simulation-based decision making procedure which can be applied in real-time management situations. We have used this novel simulation-optimization technique to study several disaster response problems. The methodologies provided herein should be useful to professionals and researchers in the fields of industrial engineering and operations research. The applications in disaster response management should help emergency managers and personnel to gain insights into several significant response problems.

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