Idol-Guided Backtracking Search Optimization Algorithm
نویسندگان
چکیده
This paper introduces a new variant of the Backtracking Search Optimization Algorithm (BSA) in order to improve the quality of the solutions found by the algorithm. The proposed algorithm is called Idol-Guided Backtracking Search Optimization Algorithm (IG-BSA): it uses the historical population defined in BSA to build and update a set of idols taken from several previous generations, and the current population evolves under the influence of these idols. Moreover, in contrast with BSA, we add a diversification strategy in case of stagnation. An experimental study with 19 widely used benchmark problems is presented. Numerical results and statistical tests show that IG-BSA outperforms BSA, CMAES, and SPSO2011.
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