Biomimetics, Journal Year: 2025, Volume and Issue: 10(5), P. 260 - 260
Published: April 23, 2025
In real-world applications, many complex problems can be formulated as mathematical optimization challenges, and efficiently solving these is critical. Metaheuristic algorithms have proven highly effective in addressing a wide range of engineering issues. The differentiated creative search recently proposed evolution-based meta-heuristic algorithm with certain advantages. However, it also has limitations, including weakened population diversity, reduced efficiency, hindrance comprehensive exploration the solution space. To address shortcomings DCS algorithm, this paper proposes multi-strategy (MSDCS) based on collaborative development mechanism evaluation strategy. First, that organically integrates estimation distribution to compensate for algorithm’s insufficient ability its tendency fall into local optimums through guiding effect dominant populations, improve quality efficiency at same time. Secondly, new strategy realize coordinated transition between exploitation fitness distance. Finally, linear size reduction incorporated DCS, which significantly improves overall performance by maintaining large initial stage enhance capability extensive space, then gradually decreasing later capability. A series validations was conducted CEC2018 test set, experimental results were analyzed using Friedman Wilcoxon rank sum test. show superior MSDCS terms convergence speed, stability, global optimization. addition, successfully applied several constrained problems. all cases, outperforms basic fast strong robustness, emphasizing efficacy practical applications.
Language: Английский