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Titlebook: Evolutionary Computation for Dynamic Optimization Problems; Shengxiang Yang,Xin Yao Conference proceedings 2013 Springer-Verlag Berlin Hei

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书目名称Evolutionary Computation for Dynamic Optimization Problems
编辑Shengxiang Yang,Xin Yao
视频video
概述Compilation on the state-of-the-art of evolutionary computation for dynamic optimization problems.Valuable reference book for the domain of Evolutionary Computation for Dynamic Optimization Problems i
丛书名称Studies in Computational Intelligence
图书封面Titlebook: Evolutionary Computation for Dynamic Optimization Problems;  Shengxiang Yang,Xin Yao Conference proceedings 2013 Springer-Verlag Berlin Hei
描述.This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. .Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation..
出版日期Conference proceedings 2013
关键词Computational Intelligence; Dynamic Optimization Problems; Evolutionary Algorithms; Hybrid Intelligent
版次1
doihttps://doi.org/10.1007/978-3-642-38416-5
isbn_softcover978-3-642-44843-0
isbn_ebook978-3-642-38416-5Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2013
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https://doi.org/10.1007/978-3-658-12252-2ected, knowledge acquired from the old environment is stored in order to recall it whenever the same state reappears. We illustrate our study by presenting several experiments and compare our results to those of standard algorithms.
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Die Unternehmensethik funktioniert nicht,, we investigate a series of dynamic genetic algorithms to solve both the dynamic shortest path routing problem and the dynamic multicast routing problem in MANETs. The experimental results show that these specifically designed dynamic genetic algorithms can quickly adapt to environmental changes (i
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Genetic Algorithms for Dynamic Routing Problems in Mobile Ad Hoc Networks, we investigate a series of dynamic genetic algorithms to solve both the dynamic shortest path routing problem and the dynamic multicast routing problem in MANETs. The experimental results show that these specifically designed dynamic genetic algorithms can quickly adapt to environmental changes (i
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https://doi.org/10.1007/978-3-642-17950-1e to the importance in real-world applications. A variety of evolutionary computation approaches have been developed to address DOPs. In parallel with developing new approaches, many benchmark and real-world DOPs have been constructed and used to compare them under different performance measures. In
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MedR Schriftenreihe Medizinrechtn evolutionary computation (EC) in terms of the number of activities and publications. This chapter provides a summary of main EDO approaches in solving DOPs. The strength and weakness of each approach and their suitability for different types of DOPs are discussed. Current gaps, challenging issues
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