Multiobjective Cloud Particle Optimization Algorithm Based on Decomposition
AbstractThe multiobjective evolutionary algorithm based on decomposition (MOEA/D) has received attention from researchers in recent years. This paper presents a new multiobjective algorithm based on decomposition and the cloud model called multiobjective decomposition evolutionary algorithm based on Cloud Particle Differential Evolution (MOEA/D-CPDE). In the proposed method, the best solution found so far acts as a seed in each generation and evolves two individuals by cloud generator. A new individual is produced by updating the current individual with the position vector difference of these two individuals. The performance of the proposed algorithm is carried on 16 well-known multi-objective problems. The experimental results indicate that MOEA/D-CPDE is competitive. View Full-Text
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Li, W.; Wang, L.; Jiang, Q.; Hei, X.; Wang, B. Multiobjective Cloud Particle Optimization Algorithm Based on Decomposition. Algorithms 2015, 8, 157-176.
Li W, Wang L, Jiang Q, Hei X, Wang B. Multiobjective Cloud Particle Optimization Algorithm Based on Decomposition. Algorithms. 2015; 8(2):157-176.Chicago/Turabian Style
Li, Wei; Wang, Lei; Jiang, Qiaoyong; Hei, Xinhong; Wang, Bin. 2015. "Multiobjective Cloud Particle Optimization Algorithm Based on Decomposition." Algorithms 8, no. 2: 157-176.