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

Por: Colaborador(es): Tipo de material: TextoTextoEditor: Boston, MA : Springer US, 2007Descripción: xv, 317 páginas recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9780387686929
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • TA329-348
Recursos en línea:
Contenidos:
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.
Resumen: 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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Springer eBooks

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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