20.500.12556/DKUM-93008 Overcoming stagnation in metaheuristic algorithms with MsMA’s adaptive meta-level partitioning Stagnation remains a persistent challenge in optimization with metaheuristic algorithms (MAs), often leading to premature convergence and inefficient use of the remaining evaluation budget. This study introduces , a novel meta-level strategy that externally monitors MAs to detect stagnation and adaptively partitions computational resources. When stagnation occurs, divides the optimization run into partitions, restarting the MA for each partition with function evaluations guided by solution history, enhancing efficiency without modifying the MA’s internal logic, unlike algorithm-specific stagnation controls. The experimental results on the CEC’24 benchmark suite, which includes 29 diverse test functions, and on a real-world Load Flow Analysis (LFA) optimization problem demonstrate that MsMA consistently enhances the performance of all tested algorithms. In particular, Self-Adapting Differential Evolution (jDE), Manta Ray Foraging Optimization (MRFO), and the Coral Reefs Optimization Algorithm (CRO) showed significant improvements when paired with MsMA. Although MRFO originally performed poorly on the CEC’24 suite, it achieved the best performance on the LFA problem when used with MsMA. Additionally, the combination of MsMA with Long-Term Memory Assistance (LTMA), a lookup-based approach that eliminates redundant evaluations, resulted in further performance gains and highlighted the potential of layered meta-strategies. This meta-level strategy pairing provides a versatile foundation for the development of stagnation-aware optimization techniques. optimization metaheuristics stagnation meta-level strategy algorithmic performance duplicate solutions optimizacija metaheuristika stagnacija strategija meta ravni algoritemsko delovanje true true false MDPI Angleški jezik Slovenski jezik https://www.mdpi.com/2227-7390/13/11/1803 © 2025 by the authors Članek v reviji 2025-05-30 12:30:59 2025-05-30 12:30:59 2025-05-31 03:09:15 0000-00-00 00:00:00 2025 0 0 34 str. iss. 11, [article no.] 1803 Vol. 13 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-05-23 2025-05-26 2025-05-28 004.4 237771523 10.3390/math13111803 2227-7390 mathematics-13-01803-v2_(1).pdf mathematics-13-01803-v2_(1).pdf 1 5316262E0E6188188CEB1E50BC35E549 65580db94549f67f19dc886c6f24b2e6d019bab28f009e9f459bff543a419c3d 6bd5e662-3d41-11f0-adaa-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=191546 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0