An Improved NSGA-III with a Comprehensive Adaptive Penalty Scheme for Many-Objective Optimization
Xinghang Xu,
Du Cheng,
Dan Wang
et al.
Abstract:Pareto dominance-based algorithms face a significant challenge in handling many-objective optimization problems. As the number of objectives increases, the sharp rise in non-dominated individuals makes it challenging for the algorithm to differentiate their quality, resulting in a loss of selection pressure. The application of the penalty-based boundary intersection (PBI) method can balance convergence and diversity in algorithms. The PBI method guides the evolution of individuals by integrating the parallel a… Show more
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