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Improved Modified Bacterial Foraging Optimization Algorithm to Solve Constrained Numerical Optimization Problems |
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PP: 607-622 |
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doi:10.18576/amis/100220
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Author(s) |
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Betania Hernández-Ocaña,
Ma. Del Pilar Pozos-Parra,
Efrén Mezura-Montes,
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Abstract |
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| This paper presents an improved version of the modified bacterial foraging optimization algorithm to solve constrained
numerical optimization problems. Four mechanisms are added: (1) two swim operators, one to favor the exploration and another one
to focus on the exploitation of the search space, where a dynamic mechanism is considered to deal with the stepsize value, (2) a skew
mechanism for a more suitable initial swarm where bacteria are divided in three groups, two of them close to the boundaries of the
search space and one distributed in all the search space, (3) a local search operator and (4) a decrease in the usage of the reproduction
step to deal with premature convergence. 60 well-known test problems from two benchmarks are solved along three experiments. The
first experiment aims to provide preliminary evidence on the suitable behavior of the new mechanism added. The second experiment
provides an in-depth comparison of the new version against its previous one based on final results and four performance measures. The
third experiment compares the performance of the proposed algorithm against five state-of-the-art nature-inspired algorithms designed
to deal with constrained continuous search spaces. The results show that the proposed algorithm clearly provides a better performance
against its predecessor by increasing its ability to reach the feasible region and generating better solutions, while obtaining a competitive
performance against those compared state-of-the-art algorithms. |
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