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The Particle Swarm Optimization (PSO) plunges into the local minimum easily. In order to overcome this shortcoming, we propose an improved PSO algorithm with the features of linearly decreasing of inertia weight and the re-initialization of the particle when it gets stagnated. The improved PSO is a local PSO and its topology is wheels. From the experimental results of three non-linear testing functions...
The shortcomings of some existing Particle Swarm Optimization (PSO) algorithms are analyzed and an improved discrete PSO algorithm with wheels topology which updates the particles' positions by using swap operator, swap sequence and partially matched crossover based on the local PSO is proposed in the present study. A mutation process in which all the particles are reinitialized when the swarm is...
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