Evolutionary Multi-objective Optimization in Uncertain Environments

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By:"Chi-Keong Goh","Kay Chen Tan"
Published on 2009-02-03 by Springer

Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. \

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Download Evolutionary Multi-objective Optimization in Uncertain Environments PDF Books Free

Download Evolutionary Multi-objective Optimization in Uncertain Environments PDF Free

Download Evolutionary Multi-objective Optimization in Uncertain Environments Books Free

Download Evolutionary Multi-objective Optimization in Uncertain Environments PDF

Download Evolutionary Multi-objective Optimization in Uncertain Environments Books

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