Kaveh, Ali. creator author. aut http://id.loc.gov/vocabulary/relators/aut Yousefpoor, Hossein. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

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access XII, 342 p. 153 illus., 149 illus. in color. online resource. 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. 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. by Ali Kaveh, Hossein Yousefpoor. Computational intelligence Mathematical optimization Computational Intelligence Optimization Q342 9783031489181 https://doi.org/10.1007/978-3-031-48918-1 https://doi.org/10.1007/978-3-031-48918-1 240129 20251030111406.0 978-3-031-48918-1