| 书目名称 | Metaheuristic Computation: A Performance Perspective |
| 编辑 | Erik Cuevas,Primitivo Diaz,Octavio Camarena |
| 视频video | |
| 概述 | Presents the performance comparison of various metaheuristic techniques when they face complex optimization problems.Particularly focuses on recently developed algorithms.This book is designed so that |
| 丛书名称 | Intelligent Systems Reference Library |
| 图书封面 |  |
| 描述 | .This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization pro |
| 出版日期 | Book 2021 |
| 关键词 | Swarm Intelligence; Metaheuristics; Evolutionary computation; Swarm Methods; Metaheuristic Methods |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-58100-8 |
| isbn_softcover | 978-3-030-58102-2 |
| isbn_ebook | 978-3-030-58100-8Series ISSN 1868-4394 Series E-ISSN 1868-4408 |
| issn_series | 1868-4394 |
| copyright | Springer Nature Switzerland AG 2021 |
发表于 2025-3-21 19:59:11
