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- W2770398095 abstract "Artificial Bee Colony (ABC) algorithm is considered an efficient nature inspired algorithm to solve continues unconstraint optimization problems. It was developed by taking inspiration from food foraging behavior of honey bee. To get better speed of convergence in ABC, Zhu and Kwong anticipated an enhanced version of ABC, namely Gbest-guided ABC (GABC). But, both the algorithms, i.e., GABC and ABC could not perform well for solving constraints optimization problems. In this paper, a variant of GABC is proposed that may be able to solve constraint optimization problems as well as unconstraints optimization problems. In the proposed variant, namely modified GABC (MGABC), a strategy is proposed which adjusts the step size of the solutions, iteratively during the global optima search process. The competence and toughness of the newly anticipated MGABC are measured by testing it over 8 real-world complex optimization problems. The simulated results are compared with ABC, best-so-far ABC, GABC and modified ABC." @default.
- W2770398095 created "2017-12-04" @default.
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- W2770398095 date "2017-11-25" @default.
- W2770398095 modified "2023-09-24" @default.
- W2770398095 title "Modified Gbest Artificial Bee Colony Algorithm" @default.
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- W2770398095 doi "https://doi.org/10.1007/978-981-10-5687-1_59" @default.
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