Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms (Studies in Computational Intelligence) by Kay Chen Tan
Springer; 2009 edition | March 9, 2009 | English | ISBN: 3540959750 | 269 pages | PDF | 8 MB
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.
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