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Titlebook: Evolutionary Algorithms in Management Applications; J?rg Biethahn,Volker Nissen Book 1995 Springer-Verlag Berlin Heidelberg 1995 Evolution

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書目名稱Evolutionary Algorithms in Management Applications
編輯J?rg Biethahn,Volker Nissen
視頻videohttp://file.papertrans.cn/318/317817/317817.mp4
圖書封面Titlebook: Evolutionary Algorithms in Management Applications;  J?rg Biethahn,Volker Nissen Book 1995 Springer-Verlag Berlin Heidelberg 1995 Evolution
描述Evolutionary Algorithms (EA) are powerful search and optimisation techniques inspired by the mechanisms of natural evolution. They imitate, on an abstract level, biological principles such as a population based approach, the inheritance of information, the variation of information via crossover/mutation, and the selection of individuals based on fitness. The most well-known class of EA are Genetic Algorithms (GA), which have received much attention not only in the scientific community lately. Other variants of EA, in particular Genetic Programming, Evolution Strategies, and Evolutionary Programming are less popular, though very powerful too. Traditionally, most practical applications of EA have appeared in the technical sector. Management problems, for a long time, have been a rather neglected field of EA-research. This is surprising, since the great potential of evolutionary approaches for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of ad
出版日期Book 1995
關(guān)鍵詞Evolutionary Algorithms; Genetic Algorithms; Genetische Alogrithmen; Management; Planning; algorithms; dec
版次1
doihttps://doi.org/10.1007/978-3-642-61217-6
isbn_softcover978-3-642-64749-9
isbn_ebook978-3-642-61217-6
copyrightSpringer-Verlag Berlin Heidelberg 1995
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Abhandlungen zur Literaturwissenschaftspond to cutting pattern with smaller trim losses. The encoding used not only optimizes the memory required to solve the problem but simplifies the process of pattern generation. In order to evaluate the performance of this method a set of numerical experiments is performed. It is shown that this me
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,Auf der Suche nach dem erz?hlten Staat,n response to others’ actions in any week, we examine the adaptive strategic behaviour of the three largest sellers. We model the sellers’ strategic behaviours as finite automata with memory of previous weeks’ actions, and use the Axelrod/Forrest representation of the action function, mapping state
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Book 1995for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of ad
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pproaches for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of ad978-3-642-64749-9978-3-642-61217-6
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