BinBRO: Binary Battle Royale Optimizer algorithm

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 sol...

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Bibliographic Details
Published in:Expert systems with applications Vol. 195; p. 116599
Main Authors: (Rahkar Farshi), Taymaz Akan, Agahian, Saeid, Dehkharghani, Rahim
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.06.2022
Elsevier BV
Subjects:
Battle Royale Optimization algorithm
Benchmarks
Datasets
Discrete optimization
Genetic algorithms
Operations research
Optimization
Optimization algorithms
Particle swarm optimization
Problem solving
Search algorithms
Site selection
Discrete optimization
Optimization
Battle Royale Optimization algorithm
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary: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. •We proposed a binary version of Battle Royale Optimization algorithm named BinBRO.•BinBRO performs as good as or better than existing binary optimization algorithms.•BinBRO provides a good balance between exploration and exploitation.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2022.116599