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A dual-stage dual-population evolutionary algorithm using new adaptive environmental selection method for complex constrained multi-objective optimization
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DOI：10.1016/j.asoc.2025.114343.png)
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Abstract
En 中文
• A DDCEO algorithm is developed that integrates dual-stage and dualpopulation mechanisms. • The algorithm comprises a main population focused on solution feasibility and an auxiliary population that operates in two phases to enhance exploration, diversity, and convergence. • An adaptive environmental selection method retains non-dominated infeasible solutions that are positioned far from the main population yet close to the constraint boundaries, thereby accelerating the search for optimal solutions.
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