Dehkharghani, RahimAlp,S.Dehkharghani,R.Akan,T.Bhuiyan,M.A.N.2024-11-152024-11-1520240920-8542https://doi.org/10.1007/s11227-023-05676-4https://hdl.handle.net/20.500.12469/6720Battle Royale Optimizer (BRO) is a recently proposed optimization algorithm that has added a new category named game-based optimization algorithms to the existing categorization of optimization algorithms. Both continuous and binary versions of this algorithm have already been proposed. Generally, optimization problems can be divided into single-objective and multi-objective problems. Although BRO has successfully solved single-objective optimization problems, no multi-objective version has been proposed for it yet. This gap motivated us to design and implement the multi-objective version of BRO (MOBRO). Although there are some multi-objective optimization algorithms in the literature, according to the no-free-lunch theorem, no optimization algorithm can efficiently solve all optimization problems. We applied the proposed algorithm to four benchmark datasets: CEC 2009, CEC 2018, ZDT, and DTLZ. We measured the performance of MOBRO based on three aspects: convergence, spread, and distribution, using three performance criteria: inverted generational distance, maximum spread, and spacing. We also compared its obtained results with those of three state-of-the-art optimization algorithms: the multi-objective Gray Wolf optimization algorithm (MOGWO), the multi-objective particle swarm optimization algorithm (MOPSO), the multi-objective artificial vulture’s optimization algorithm (MOAVAO), the optimization algorithm for multi-objective problems (MAOA), and the multi-objective non-dominated sorting genetic algorithm III (NSGA-III). The obtained results approve that MOBRO outperforms the existing optimization algorithms in most of the benchmark suites and operates competitively with them in the others. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.eninfo:eu-repo/semantics/closedAccessBattle royale optimization algorithmBattle-royale-game-based optimization algorithmsMulti-objective problemsOptimizationMOBRO: multi-objective battle royale optimizerArticle5979601658010.1007/s11227-023-05676-42-s2.0-85174225797Q2Q2