A Modified Particle Swarm Optimization for Practical Engineering Optimization

To combine the mechanisms of the particle swarm optimization (PSO) and the genetic algorithm (GA) for global optimization problems, a modified particle swarm optimization (MPSO) was employed. In MPSO, the heuristic crossover (HC) derived from GA was modified and employed to perform local search. And then, PSO and HC generated a new position for the particle synchronously and respectively to compete in providing a new position of the particle. The approach was employed for a tension/compression string design problem and an economic dispatch problem in power system. By comparisons with the other evolutionary algorithms, the proposed approach has shown its feasibility and effectiveness.