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Sequential Approximate Multiobjective Optimization Using Computational Intelligence [electronic resource] / by Min Yoon, Yeboon Yun, Hirotaka Nakayama.

By: Contributor(s): Material type: TextTextSeries: Vector OptimizationPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: XVI, 200 p. 111 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540889106
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 003.3 23
LOC classification:
  • TA342-343
Online resources:
Contents:
Basic Concepts of Multi-objective Optimization -- Interactive Programming Methods for Multi-objective Optimization -- Generation of Pareto Frontier by Genetic Algorithms -- Multi-objective Optimization and Computational Intelligence -- Sequential Approximate Optimization -- Combining Aspiration Level Approach and SAMO -- Engineering Applications.
In: Springer eBooksSummary: This book highlights a new direction of multiobjective optimzation, which has never been treated in previous publications. When the function form of objective functions is not known explicitly as encountered in many practical problems, sequential approximate optimization based on metamodels is an effective tool from a practical viewpoint. Several sophisticated methods for sequential approximate multiobjective optimization using computational intelligence are introduced along with real applications, mainly engineering problems, in this book.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBook Available
Total holds: 0

Basic Concepts of Multi-objective Optimization -- Interactive Programming Methods for Multi-objective Optimization -- Generation of Pareto Frontier by Genetic Algorithms -- Multi-objective Optimization and Computational Intelligence -- Sequential Approximate Optimization -- Combining Aspiration Level Approach and SAMO -- Engineering Applications.

This book highlights a new direction of multiobjective optimzation, which has never been treated in previous publications. When the function form of objective functions is not known explicitly as encountered in many practical problems, sequential approximate optimization based on metamodels is an effective tool from a practical viewpoint. Several sophisticated methods for sequential approximate multiobjective optimization using computational intelligence are introduced along with real applications, mainly engineering problems, in this book.

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