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Titlebook: Genetic Algorithms + Data Structures = Evolution Programs; Zbigniew Michalewicz Book 1996Latest edition Springer-Verlag Berlin Heidelberg

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书目名称Genetic Algorithms + Data Structures = Evolution Programs
编辑Zbigniew Michalewicz
视频videohttp://file.papertrans.cn/383/382434/382434.mp4
概述Classic introduction to the evolution programming techniques.Many figures and tables.The systematic approach makes the book an appropriate text for a senior undergraduate/graduate one semester course
图书封面Titlebook: Genetic Algorithms + Data Structures = Evolution Programs;  Zbigniew Michalewicz Book 1996Latest edition Springer-Verlag Berlin Heidelberg
描述Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science..The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.
出版日期Book 1996Latest edition
关键词Optimierung; Suchalgorithmen; algorithms; data structures; evolutionary computation; genetic algorithms; g
版次3
doihttps://doi.org/10.1007/978-3-662-03315-9
isbn_softcover978-3-642-08233-7
isbn_ebook978-3-662-03315-9
copyrightSpringer-Verlag Berlin Heidelberg 1996
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Ö. Saygin,S. Gerken,B. Meyer,H. T. Witt 11.3), and the path planning problem in mobile robot environment (section 11.4). The chapter concludes with an additional section 11.5, which provides some brief remarks on a few other, interesting problems.
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Soma S. Marla,Neelofar Mirza,K. D. Nadellang on the output language, we can divide all approaches to automatic knowledge acquisition into two categories: symbolic and non-symbolic. Non-symbolic systems do not represent knowledge explicitly. For example, in statistical models knowledge is represented as a set of examples together with some s
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Progress in Inertial Fusion Researchs maintain a population of potential solutions, they have some selection process based on fitness of individuals, and some “genetic” operators. One type of such systems is a class of Evolution Strategies i.e., algorithms which imitate the principles of natural evolution for parameter optimization pr
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Integral Points on the Circle , + , = , — a template allowing exploration of similarities among chromosomes. A schema is built by introducing a . symbol (⋆) into the alphabet of genes. A schema represents all strings (a hyperplane, or subset of the search space), which match it on all positions other than ‘⋆’.
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