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MultiObjective Optimization Using Evolutionary Algorithms,Used
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Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many realworld search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and indepth discussion Includes many applications to realworld problems, including engineering design and scheduling Includes discussion of advanced topics and future research Can be used as a course text or for selfstudy Accessible to those with limited knowledge of classical multiobjective optimization and evolutionary algorithmsThe integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multiobjective optimization, allowing use as a graduate course text or for selfstudy.
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