Elitist multiobjective evolutionary algorithm for environmental/economic dispatch

Abstract

The environmental/economic dispatch problem is a multiobjective nonlinear optimization problem with constraints. Until recently, this problem has been addressed by considering economic and emission objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary algorithms can find multiple Pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. We use an elitist multiobjective evolutionary algorithm based on the nondominated sorting genetic algorithm-II (NSGA-II) for solving the environmental/economic dispatch problem. Elitism ensures that the population best solution does not deteriorate in the next generations. Simulation results are presented for a sample power system.