A dynamic dual-population co-evolutionary algorithm for constrained multi-objective optimization problems

A novel multi-population evolutionary algorithm based on two-stage division and diversity enhancement for constrained multi-objective optimization

A two-stage multi-population evolutionary algorithm with dynamic collaboration for constrained multi-objective optimization problems

Multi-objective narwhal optimizer: a novel algorithm for multi-criterion optimization

The proposed Multi-Objective Narwhal Optimizer (MONO), a Pareto-based extension of the recently developed Narwhal Optimizer, incorporates Pareto dominance, external archive management, adaptive multi-leader guidance, and crowding-distance-based diversity preservation to effectively balance convergence and exploration t...

Information-assisted solution generation based dual population constrained multi-objective evolutionary algorithm

A general hybrid framework for many-objective optimization: integrating local search into reference-vector-based evolutionary algorithms

Results show that integrating local search significantly enhances performance, while a principled method for setting hybrid parameters ensures robustness and reproducibility, highlighting the potential of combining mathematical programming techniques with evolutionary algorithms for high-dimensional many-objective opti...

A Two-Stage Many-Objective Evolutionary Algorithm with Survival-Ratio-Based Switching

Many-objective optimization problems (MaOPs) suffer from weakened selection pressure as the number of objectives increases, making it difficult to balance convergence and diversity. Existing two-stage and multi-stage many-objective evolutionary algorithms (MaOEAs) often determine stage transitions using preset schedule...