Enhancing particle swarm optimization using generalized opposition-based learning

  title={Enhancing particle swarm optimization using generalized opposition-based learning},
  author={Hui Wang and Zhijian Wu and Shahryar Rahnamayan and Yong Liu and Mario Ventresca},
  journal={Inf. Sci.},
Particle swarm optimization (PSO) has been shown to yield good performance for solving various optimization problems. However, it tends to suffer from premature convergence when solving complex problems. This paper presents an enhanced PSO algorithm called GOPSO, which employs generalized opposition-based learning (GOBL) and Cauchy mutation to overcome this problem. GOBL can provide a faster convergence, and the Cauchy mutation with a long tail helps trapped particles escape from local optima… CONTINUE READING
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