Multi-objective Hybrid Differential Evolution Algorithm Based on Pareto Optimal Solution Migration

By using differential evolution algorithm (DE) to solve multi-objective optimization problems, Pareto optimal solution migration based differential evolution for multi-objective optimization (PSDEMO) is proposed. The elitist strategy is adopted in the algorithm. Pareto non-dominated solutions found in the evolution operation are archived dynamically with the evolution process, and all the non-dominated solutions in the archive are applied to migration operation after mutation and crossover operations of DE are finished. Compared with standard DE, simulation results show the PSDEMO not only helps to improve quantity of the Pareto non-dominated solutions, but also helps to enhance quality of the Pareto non-dominated solutions, it also has good balance keeping ability between diversity and convergence.