Ordinal Optimization [electronic resource] : Soft Optimization for Hard Problems / by Yu-Chi Ho, Qian-Chuan Zhao, Qing-Shan Jia.

By: Ho, Yu-Chi [author.]Contributor(s): Zhao, Qian-Chuan [author.] | Jia, Qing-Shan [author.] | SpringerLink (Online service)Material type: TextTextLanguage: English Publisher: Boston, MA : Springer US, 2007Description: XV, 317 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780387686929Subject(s): Computer science | Engineering mathematics | Engineering | Computer engineering | Computer Science | Appl.Mathematics/Computational Methods of Engineering | Computational Intelligence | Electrical Engineering | Control, Robotics, Mechatronics | Operations Research/Decision TheoryAdditional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
Ordinal Optimization Fundamentals -- Comparison of Selection Rules -- Vector Ordinal Optimization -- Constrained Ordinal Optimization -- Memory Limited Strategy Optimization -- Additional Extensions of the OO Methodology -- Real World Application Examples.
In: Springer eBooksSummary: Performance evaluation of increasingly complex human-made systems requires the use of simulation models. However, these systems are difficult to describe and capture by succint mathematical models. The purpose of this book is to address the difficulties of the optimization of complex systems via simulation models or other computation-intensive models involving possible stochastic effects and discrete choices. This book establishes distinct advantages of the "softer" ordinal approach for search-based type problems, analyzes its general properties, and shows the many orders of magnitude improvement in computational efficiency that is possible.
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Ordinal Optimization Fundamentals -- Comparison of Selection Rules -- Vector Ordinal Optimization -- Constrained Ordinal Optimization -- Memory Limited Strategy Optimization -- Additional Extensions of the OO Methodology -- Real World Application Examples.

Performance evaluation of increasingly complex human-made systems requires the use of simulation models. However, these systems are difficult to describe and capture by succint mathematical models. The purpose of this book is to address the difficulties of the optimization of complex systems via simulation models or other computation-intensive models involving possible stochastic effects and discrete choices. This book establishes distinct advantages of the "softer" ordinal approach for search-based type problems, analyzes its general properties, and shows the many orders of magnitude improvement in computational efficiency that is possible.

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