Memetic Algorithm for Economic Dispatch with Nonsmooth Cost Functions

This paper presents a new approach to economic dispatch (ED) problems with nonconvex cost functions using Memetic Algorithm (MA). The practical ED problem have nonconvex cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. In this paper, MA with three different local searches is suggested to deal with the equality and inequality constraints in the ED problem. To validate the results obtained by proposed MAs, a Real Genetic Algorithm (RGA) and an MA adopted from the literature are applied for comparison. Also, the results obtained by MAs and RGA are compared with the previous approaches reported in the literature. The results show that the MAs produce optimal or nearly optimal solutions for all study systems.