Solving constrained optimization using multiple swarm cultural PSO with inter-swarm communication

In this study, a novel cultural-based constrained particle swarm optimization (CPSO) is proposed that incorporates the information of the objective function and constraints violation into four sections of the belief space, that is normative knowledge, spatial knowledge, situational knowledge, and temporal knowledge. The stored information facilitates the communication among swarms in the population space. It also assists in selecting the leading particles using a three-level PSO: personal, swarm and global levels. Simulation results of the proposed heuristics over a number of benchmark problems demonstrate that this novel cultural framework helps the multiple swarm CPSO to perform very efficiently.