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  <titleInfo>
    <title>Multi-objective optimization using evolutionary algorithms</title>
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  <name type="personal">
    <namePart>Deb, Kalyanmoy.</namePart>
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    <place>
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    <publisher>Wiley</publisher>
    <dateIssued>2005</dateIssued>
    <dateIssued encoding="marc">2009</dateIssued>
    <edition>1st ed.</edition>
    <issuance>monographic</issuance>
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    <extent>544 p. ; 25 cm.</extent>
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  <abstract>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. Comrephensive coverage of this growing area of research. Carefully introduces each algorithm with examples and in-depth discussion. Includes many applications to real-world problems, including engineering design and scheduling. Includes discussion of advanced topics and future research. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms 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.</abstract>
  <note type="statement of responsibility">Kalyanmoy Deb.</note>
  <identifier type="isbn">0470743611 (paperback)</identifier>
  <identifier type="isbn">9780470743614 (paperback)</identifier>
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