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The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Evolutionary algorithms are very powerful techniques used to find solutions to real-world 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. This title provides comprehensive coverage of this growing area of research. It carefully introduces each algorithm with examples and in-depth discussion. It also includes many applications to real-world problems, including engineering design and scheduling. It also includes discussion of advanced topics and future research. It is accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. It provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches. This integrated presentation of theory, algorithms and examples will benefit those working in the areas of optimization, optimal design and evolutionary computing.
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The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Evolutionary algorithms are very powerful techniques used to find solutions to real-world 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. This title provides comprehensive coverage of this growing area of research. It carefully introduces each algorithm with examples and in-depth discussion. It also includes many applications to real-world problems, including engineering design and scheduling. It also includes discussion of advanced topics and future research. It is accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms. It provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches. This integrated presentation of theory, algorithms and examples will benefit those working in the areas of optimization, optimal design and evolutionary computing.