Improved MOPSO Based on ε-domination

Designing efficient algorithms for multi-objective optimization problems (MOPs) is a very challenging problem. In this paper, based on the previously proposed eDMOPSO, an improved multi-objective PSO with orthogonal design and crossover is proposed. Firstly, the orthogonal design is used to generate the initial swarm, which makes the algorithm evenly scan the feasible solution space to find good points (solution) for the further exploration in subsequent iterations. Secondly, to explore the search space efficiently and get the good solutions in objective space, a new crossover operator is designed. Finally, Simulation experiments on the disabled benchmark problems of eDMOPSO show the proposed strategies are efficient.

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