Chaotic Meta-heuristic Algorithms for Optimal Design of Structures

Bibliographic Details
Main Authors: Kaveh, Ali (Author), Yousefpoor, Hossein (Author)
Corporate Author: SpringerLink (Online service)
Summary:XII, 342 p. 153 illus., 149 illus. in color.
text
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edition:1st ed. 2024.
Series:Studies in Computational Intelligence, 1129
Subjects:
Online Access:https://doi.org/10.1007/978-3-031-48918-1
Format: Electronic Book

MARC

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490 1 |a Studies in Computational Intelligence,  |x 1860-9503 ;  |v 1129 
505 0 |a Introduction -- Chaotic Maps and Meta-Heuristic Algorithms -- Chaotic Cyclical Parthenogenesis Algorithm -- Chaotic Teaching Learning-Based Optimization -- Chaotic Biogeography Based Optimization -- Chaotic Differential Evolution -- Chaotic Water Evaporation Optimization -- Chaotic Artificial Bees Colony -- Chaotic Imperialist Competitive Algorithm. 
520 |a In this book, various chaos maps are embedded in eleven efficient and well-known metaheuristics and a significant improvement in the optimization results is achieved. The two basic steps of metaheuristic algorithms consist of exploration and exploitation. The imbalance between these stages causes serious problems for metaheuristic algorithms, which are immature convergence and stopping in local optima. Chaos maps with chaotic jumps can save algorithms from being trapped in local optima and lead to convergence toward global optima. Embedding these maps in the exploration phase, exploitation phase, or both simultaneously corresponds to three efficient and useful scenarios. By creating competition between different modes and increasing diversity in the search space and creating sudden jumps in the search phase, improvements are achieved for chaotic algorithms. Four Chaotic Algorithms, including Chaotic Cyclical Parthenogenesis Algorithm, Chaotic Water Evaporation Optimization, Chaotic Tug-of-War Optimization, and Chaotic Thermal Exchange Optimization are developed. 
532 8 |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. 
532 8 |a No reading system accessibility options actively disabled 
532 8 |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com 
650 0 |a Computational intelligence. 
650 0 |a Mathematical optimization. 
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