Adaptive multi-region multi-directional competitive swarm optimizer algorithm for large-scale multi-objective problems

Key Points

• Optimization improves across varying objectives using the competitive swarm optimizer, and efficiency is seen in large-scale applications.
• The method enhances performance by balancing between exploration and exploitation of potential solutions across multiple regions.
• Adaptive techniques adjust the swarm's behavior based on the problem landscape, ensuring a dynamic optimization process.
• Future applications may benefit from this algorithm, which shows significant promise in tackling complex optimization tasks.