| 书目名称 | Evolutionary Scheduling | | 编辑 | Keshav P. Dahal,Kay Chen Tan,Peter I. Cowling | | 视频video | | | 概述 | Demonstrate the applicability of evolutionary computational techniques to solve scheduling problems | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | .Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems. The intended readers | | 出版日期 | Book 2007 | | 关键词 | Computational Intelligence; Evolution; Evolutionary Algorithms; Fuzzy; Operations Research; algorithm; art | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-540-48584-1 | | isbn_softcover | 978-3-642-08017-3 | | isbn_ebook | 978-3-540-48584-1Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | Springer-Verlag Berlin Heidelberg 2007 |
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发表于 2025-3-21 18:55:40
