Network-Structured Particle Swarm Optimizer considering neighborhood relationships

This study proposes a new network-structured particle swarm optimizer considering neighborhood relationships (NS-PSO). All particles of NS-PSO are connected to adjacent particles by a neighborhood relation of the 2-dimensional network. The directly connected particles share the information of their own best position. Each particle is updated depending on the neighborhood distance on the network between it and a winner, whose function value is best among all particles. Simulation results show the searching efficiency of NS-PSO.