| 期刊全称 | Biologically-Inspired Optimisation Methods | | 期刊简称 | Parallel Algorithms, | | 影响因子2023 | Andrew Lewis,Sanaz Mostaghim,Marcus Randall | | 视频video | | | 发行地址 | Presents recent research in Biologically-inspired Optimisation Methods | | 学科分类 | Studies in Computational Intelligence | | 图书封面 |  | | 影响因子 | Humanity has often turned to Nature for inspiration to help it solve its problems. The systems She provides are often based on simple rules and premises, yet are able to adapt to new and complex environments quickly and efficiently. Problems from a range of human endeavours, including, science, engineering and economics, require us to find good quality solutions in exponentially large search spaces, a task that often requires vast amounts computational resources and effort. In this book, the contributing authors solve these problems by modelling aspects of the natural world, from the flocking of birds and fish, the operation of colonies of ants through to chromosome reproduction and beyond. Many of the contributions represent extended studies of work presented at a number of workshops on Biologically-Inspired Optimisation Methods at international conferences on e-Science, Grid Computing, and Evolutionary Computation. A variety of chapters from some of the leading experts in the field present an overview of the state-of-the-art, recent advances in theoretical and practical ideas and techniques, and details of application of these methods to a range of benchmark and real world p | | Pindex | Book 2009 |
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发表于 2025-3-21 17:56:09
