A Modified Particle Swarm Optimization for Economic Dispatch Problems with Non-Smooth Cost Functions

This study proposes a new versatile optimization algorithm called modified particle swarm optimization algorithm (MPSO) for solving economic dispatch problems (ED) with non smooth objective functions. In this algorithm, particles not only studies from itself and the best one but also from other individuals. By this enhanced study behavior, the opportunity to find the global optimum is increased and the influence of the initial position of the particles is decreased. To show its efficiency and effectiveness, the MPSO is applied to sample ED problems with smooth cost function as well as non-smooth cost functions. The results of the MPSO are compared with those of the conventional numerical method, evolutionary programming approach and the classical PSO approach.