Current position-based Fitness Euclidean-distance Ratio Particle Swarm Optimizer for multi-modal optimization

In this paper, the nonlinear constrained multi-objective environmental economic dispatch (EED) problem is solved using fast multi-objective evolutionary programming (FMOEP). Due to the global warming by fossil fuel, environmental concern becomes more and more important in recent years. The purpose of multi-objective optimization algorithm is minimizing all the different objectives simultaneously and finds the best tradeoff solution for this environmental/economic dispatch problem. In order to evaluate the performance of FMOEP on EED problems, the standard IEEE 30-bus six-generator test system is studied. The performance is compared against NSGAII and a number of results reported in literature. The results show that the FMOEP is effective in solving EED problems.