Adaptive elite learning particle swarm optimization algorithm with complementary sub-strategies for multimodal problems

Key Points

• The adaptive elite learning particle swarm optimization algorithm significantly enhances performance in multimodal problems.
• Key metrics indicate notable improvements in convergence speed and solution quality using the proposed algorithm.
• Observational analysis highlights the effectiveness of complementary sub-strategies in optimizing complex multimodal challenges.
• This approach suggests strong potential applications in various fields, though additional validation is necessary.