A Coevolutionary Paradigm for Dynamic Multi-Objective Optimization

As pointed out in the previous chapter, it is imperative that the MOEA must be capable of attaining high convergence speeds in order to find the optimal solution set before it changes and becomes obsolete. However, high convergence speed often implies a rapid loss of diversity during the optimization process, which inevitably leads to the inability to track the dynamic Pareto front. Therefore, it is necessary to maintain or generate sufficient diversity to explore the search space when the multi-objective problem changes.