Exploitation and Comparison of Computational Intelligence Techniques on the Feature Selection Problem

Kalayci, Gülşah Tarakçi; Alkaya, Ali Fuat; Algin, Ramazan

doi:10.1007/978-3-030-23756-1_146

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Recently, MBO is applied to the feature selection problem where it is compared with some metaheuristic approaches and it is shown that MBO outperforms others (Algin et al, 2020;Kalayci et al, 2019).…”

Section: Mbo and Related Previous Workmentioning

confidence: 99%

Enhanced migrating birds optimization algorithm for optimization problems in different domains

Algin,

Alkaya,

Agaoglu

2024

Ann Oper Res

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Migrating birds optimization algorithm is a promising metaheuristic algorithm recently introduced to the optimization community. In this study, we propose a superior version of the migrating birds optimization algorithm by hybridizing it with the simulated annealing algorithm which is one of the most popular metaheuristics. The new algorithm, called MBOx, is compared with the original migrating birds optimization and four well-known metaheuristics, including the simulated annealing, differential evolution, genetic algorithm and recently proposed harris hawks optimization algorithm. The extensive experiments are conducted on problem instances from both discrete and continuous domains; feature selection problem, obstacle neutralization problem, quadratic assignment problem and continuous functions. On problems from discrete domain, MBOx outperforms the original MBO and others by up to 20.99%. On the continuous functions, it is observed that MBOx does not lead the competition but takes the second position. As a result, MBOx provides a significant performance improvement and therefore, it is a promising solver for computational optimization problems.

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Section: Mbo and Related Previous Workmentioning

confidence: 99%