Abstract
Designing efficient algorithms for multi-objective optimization problems (MOPs) is a very challenging problem. In this paper, based on the previously proposed εDMOPSO, 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 εDMOPSO show the proposed strategies are efficient.
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Liu, Y., Niu, B., Sui, C., Liu, M. (2012). Improved MOPSO Based on ε-domination. In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_23
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DOI: https://doi.org/10.1007/978-3-642-31576-3_23
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