BinBRO: Binary Battle Royale Optimizer algorithm

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Tarih

2022-02-04

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Elsevier Ltd

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info:eu-repo/semantics/closedAccess

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Özet

Stochastic methods attempt to solve problems that cannot be solved by deterministic methods with reasonable time complexity. Optimization algorithms benefit from stochastic methods; however, they do not guarantee to obtain the optimal solution. Many optimization algorithms have been proposed for solving problems with continuous nature; nevertheless, they are unable to solve discrete or binary problems. Adaptation and use of continuous optimization algorithms for solving discrete problems have gained growing popularity in recent decades. In this paper, the binary version of a recently proposed optimization algorithm, Battle Royale Optimization, which we named BinBRO, has been proposed. The proposed algorithm has been applied to two benchmark datasets: the uncapacitated facility location problem, and the maximum-cut graph problem, and has been compared with 6 other binary optimization algorithms, namely, Particle Swarm Optimization, different versions of Genetic Algorithm, and different versions of Artificial Bee Colony algorithm. The BinBRO-based algorithms could rank first among those algorithms when applying on all benchmark datasets of both problems, UFLP and Max-Cut.

Açıklama

Anahtar Kelimeler

Battle Royale Optimization algorithm, Benchmark datasets, Computational complexity, Discrete optimization, Discrete problems, Deterministic methods, Genetic algorithms, Optimization, Optimisations, Optimization algorithms, Optimizers, Particle swarm optimization (PSO), Stochastic methods, Stochastic systems, Time complexity, Bee colony algorithm, Search

Kaynak

Expert Systems with Applications

WoS Q Değeri

Q1
Q1

Scopus Q Değeri

Q1

Cilt

195

Sayı

Künye

(Rahkar Farshi), T. A., Agahian, S. & Dehkharghani, R. (2022). BinBRO: Binary Battle Royale Optimizer algorithm. Expert Systems with Applications, 195, 1-13. doi:10.1016/j.eswa.2022.116599