Kaveh A. Chaotic Meta-heuristic Algorithms for Optimal Design of Structures 2024
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Kaveh A. Chaotic Meta-heuristic Algorithms for Optimal Design of Structures 2024
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Optimization of non-linear and non-convex modes is one of the most used scien tific problems in recent decades. In order to increase the efficiency of meta-heuristic algorithms, the technology related to embedding chaotic systems in the exploration and exploitation parts of these algorithms brings significant progress. By embed ding chaotic time series, premature convergence of algorithms is prevented and local optima converge towards global optima. By creating chaotic jumps in the two impor tant phases of exploration and exploitation, chaotic series saves them from the trap of local optima and creates a balance between the phases of exploration and exploita tion. According to the inspiration of the algorithms, these series may be needed only in the stages of exploration or exploitation, or in some cases, we will need them in both stages at the same time. Therefore, the existence of chaoite’s series with different behaviors and triple scenarios, has brought huge research to introduce the best chaotic series and the best suitable scenario for each meta-heuristic algorithm.
In this research, different time series are embedded on a large number of well-known meta-heuristic algorithms and after the competition between local optima, the best of them has been introduced as the sub global optimum. In Chap. 1, there is a brief introduction to the introduction of selected algorithms for embedding chaos series. In Chap. 2, by introducing chaotic systems and examining the Lorenz absorber system, the method of embedding chaotic systems in meta-heuristic algorithms has been investigated. In Chaps. 3–13, chaos series are embedded in a large number of well known meta-heuristic algorithms and chaotic algorithms are formed. These chaotic meta-heuristic algorithms are:
Chapter 3: Chaotic Cyclical Parthenogenesis Algorithm (CCPA)
Chapter 4: Chaotic Teaching-Learning-Based Optimization (CTLBO)
Chapter 5: Chaotic Biogeography-Based optimization (CBBO)
Chapter 6: Chaotic Differential Evolution (CDE)
Chapter 7: Chaotic Water Evaporation Optimization (CWEO)
Chapter 8: Chaotic Artificial Bees Colony (CABC)
Chapter 9: Chaotic Imperialist Competitive Algorithm (CICA)
Chapter 10: Chaotic Shuffled Frog-Leaping Algorithm (CSFLA)
Chapter 11: Chaotic Particle Swarm Optimization (CPSO)
Chapter 12: Chaotic Tug-of-War Optimization (CTWO)
Chapter 13: Chaotic Thermal Exchange Optimization (CTEO)