A Novel Decomposition-Based Multi-Objective Symbiotic Organism Search Optimization Algorithm

نویسندگان

چکیده

In this research, the effectiveness of a novel optimizer dubbed as decomposition-based multi-objective symbiotic organism search (MOSOS/D) for problems was explored. The proposed based on organisms’ (SOS), which is star-rising metaheuristic inspired by natural phenomenon symbioses among living organisms. A decomposition framework incorporated in SOS stagnation prevention and its deep performance analysis real-world applications. investigation included both qualitative quantitative analyses MOSOS/D metaheuristic. For analysis, statistically examined using it to solve unconstrained DTLZ test suite real-parameter continuous optimizations. Next, two constrained structural benchmarks optimization scenario were also tackled. performed characteristics Pareto fronts, boxplots, dimension curves. To check robustness optimizer, comparative carried out with four state-of-the-art optimizers, viz., MOEA/D, NSGA-II, MOMPA MOEO, grounded six widely accepted measures. feasibility Friedman’s rank demonstrates dominance over other compared techniques exhibited solving large complex problems.

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ژورنال

عنوان ژورنال: Mathematics

سال: 2023

ISSN: ['2227-7390']

DOI: https://doi.org/10.3390/math11081898