Nature-inspired optimization algorithms / Xin-She Yang, Middlesex University London, School of Science and Technology, London, United Kingdom.
| Author/creator | Yang, Xin-She |
| Format | Electronic |
| Edition | Second edition. |
| Publication Info | London, United Kingdom ; San Diego, CA, United States : Academic Press, an imprint of Elsevier, [2021] |
| Description | xvii, 292 pages : illustrations ; 24 cm |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Supplemental Content | Full text available from eBook - Engineering 2021 [EBCE21] |
| Subjects |
| Abstract | "Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2020951293 |
| ISBN | 9780128219867 (paperback) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | ✔ Available |