Inspired by the concept of divide-and-conquer, existing multi-task/ multi-population constraint evolutionary algorithms (CMOEAs) have often employed an auxiliary population that disregards all constraints in order to simplify the problem. However, when dealing with complex Constraint Pareto Fronts (CPF), many existing approaches encounter difficulties in maintaining diversity and avoiding local optima. To address the above issue, the Three-role-community based CMOEA (TRC) which focuses on roles within the population is introduced to eliminate the burden of knowledge transfer between multi-task...
