ICCK Transactions on Swarm and Evolutionary Learning
ISSN: 3069-2962 (Online)
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TY - JOUR AU - Akan, Taymaz AU - Zálabský, Tomáš AU - Shirini, Kimia AU - Ramos-Frutos, Jorge AU - Oliva, Diego AU - Bhuiyan, Mohammad A. PY - 2026 DA - 2026/02/02 TI - Battle Royale Optimizer with Ring Neighborhood Topology JO - ICCK Transactions on Swarm and Evolutionary Learning T2 - ICCK Transactions on Swarm and Evolutionary Learning JF - ICCK Transactions on Swarm and Evolutionary Learning VL - 2 IS - 1 SP - 19 EP - 40 DO - 10.62762/TSEL.2025.751954 UR - https://www.icck.org/article/abs/TSEL.2025.751954 KW - Battle royale optimization KW - ring topology KW - optimization AB - Recently, battle royale optimizer (BRO), a game-based metaheuristic search algorithm, has been proposed for continuous optimization, inspired by a genre of digital games known as "battle royale." In BRO, each individual chooses the nearest opponent as a competitor. For this purpose, the Euclidean distance between individuals is calculated. This interaction corresponds to an increase in computational complexity by a factor of n. To improve the computational complexity of BRO, a modified methodology is proposed using a ring topology, namely, BRO-RT. In the modified version, a set of individuals is arranged in a ring such that each has a neighborhood comprising several individuals to its left and right. Instead of a pairwise comparison with all individuals in the population, the best individual among the left and right neighborhoods is selected as the competitor. We compared the proposed scheme with the original BRO and six popular optimization algorithms. All algorithms are tested in several benchmark functions and engineering optimization problems. Experimental results show that the BRO-RT demonstrates competitive performance compared to nine state-of-the-art methods across most benchmark functions. Additionally, the compression spring design problem was utilized to assess the proposed method's ability to solve real-world engineering problems. These results demonstrate that BRO-RT yields promising results when applied to real-world engineering problems. Finally, while BRO is ranked first and BRO-RT second, they achieved competitive results; BRO-RT has the advantages of lower computational complexity and faster run times than the original BRO algorithm. SN - 3069-2962 PB - Institute of Central Computation and Knowledge LA - English ER -
@article{Akan2026Battle,
author = {Taymaz Akan and Tomáš Zálabský and Kimia Shirini and Jorge Ramos-Frutos and Diego Oliva and Mohammad A. Bhuiyan},
title = {Battle Royale Optimizer with Ring Neighborhood Topology},
journal = {ICCK Transactions on Swarm and Evolutionary Learning},
year = {2026},
volume = {2},
number = {1},
pages = {19-40},
doi = {10.62762/TSEL.2025.751954},
url = {https://www.icck.org/article/abs/TSEL.2025.751954},
abstract = {Recently, battle royale optimizer (BRO), a game-based metaheuristic search algorithm, has been proposed for continuous optimization, inspired by a genre of digital games known as "battle royale." In BRO, each individual chooses the nearest opponent as a competitor. For this purpose, the Euclidean distance between individuals is calculated. This interaction corresponds to an increase in computational complexity by a factor of n. To improve the computational complexity of BRO, a modified methodology is proposed using a ring topology, namely, BRO-RT. In the modified version, a set of individuals is arranged in a ring such that each has a neighborhood comprising several individuals to its left and right. Instead of a pairwise comparison with all individuals in the population, the best individual among the left and right neighborhoods is selected as the competitor. We compared the proposed scheme with the original BRO and six popular optimization algorithms. All algorithms are tested in several benchmark functions and engineering optimization problems. Experimental results show that the BRO-RT demonstrates competitive performance compared to nine state-of-the-art methods across most benchmark functions. Additionally, the compression spring design problem was utilized to assess the proposed method's ability to solve real-world engineering problems. These results demonstrate that BRO-RT yields promising results when applied to real-world engineering problems. Finally, while BRO is ranked first and BRO-RT second, they achieved competitive results; BRO-RT has the advantages of lower computational complexity and faster run times than the original BRO algorithm.},
keywords = {Battle royale optimization, ring topology, optimization},
issn = {3069-2962},
publisher = {Institute of Central Computation and Knowledge}
}
ICCK Transactions on Swarm and Evolutionary Learning
ISSN: 3069-2962 (Online)
Email: [email protected]
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