Abstract
The combination of meta-heuristic algorithms with chaos map creates a significant improvement in the optimal design of truss structures. The main reason for this success is to balance the key stages of exploration and exploitation. Some meta-heuristic algorithms need to be improved for the exploration phase and others need to be improved for the exploitation phase. Also, in a limited number of algorithms, both steps need to be improved. Truss shape and cross-sectional optimization involves nonlinear and non-convex modes, often with several local optima. Chaos maps play a major role in escaping these local optima and achieving global optimization. Accordingly, chaotic maps prevent premature convergence and accelerate access to global optimizations by expanding the search points in scattered parts of the decision space and carefully examining the neighborhood of these points. In this study, logistic and Gauss chaos maps are incorporated in four meta-heuristic algorithms providing suitable conditions to improve the optimization results. These chaotic algorithms include Chaotic Water Evaporation Optimization (CWEO), Chaotic Artificial Bee Colony (CABC), Chaotic Imperialist Competitive Algorithm (CICA) and Chaotic Shuffled Frog-Leaping Algorithm (CSFLA).
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Kaveh, A., Zarfam, P., Aziminejad, A. et al. Comparison of Four Chaotic Meta-Heuristic Algorithms for Optimal Design of Large-Scale Truss Structures. Iran J Sci Technol Trans Civ Eng 46, 4067–4091 (2022). https://doi.org/10.1007/s40996-022-00908-8
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DOI: https://doi.org/10.1007/s40996-022-00908-8