A novel multi-objective competitive swarm optimization algorithm for multi-modal multi objective problems

With the combination of multi-objective optimization problems and practical application, it is important to find as many Pareto optimal solutions as possible for solving multi-objective optimization problems. In many real world cases, different decision makers may tend to make choices from various aspects, which leads to the generation of multi-modal optimization problems. Such featured problems may include multiple Pareto solutions in the decision space corresponding to the same objective value in the objective space, remarkably challenging the conventional solvers. In this paper, a novel multi-objective multi-modal optimization algorithm named MO_Ring_CSO_SCD is proposed based on a recent proposed meta-heuristic method competitive swarm optimizer algorithm. It also combines the ring topology, non-dominated sort strategy and special crowding distance approach. Numerical experiments were conducted on 11 multi-modal test functions and the proposed optimization algorithm has been compared with other counterparts. The results show that the proposed algorithm has competitive performance in solving the multi-objective multi-modal problem.