An enhanced non-dominated sorting based fruit fly optimization algorithm for solving environmental economic dispatch problem

A fruit fly optimization algorithm based on the enhanced non-dominated sorting (ESFOA) is proposed to solve the environmental economic dispatch (EED) problem. To measure the difference between two non-dominated solutions, the concept of the enhanced non-dominance is defined, and the degrees of dominance and non-dominance are presented. To enhance the parallel search ability, multiple fruit flies groups are used to perform evolutionary search in the ESFOA. In the vision-based search process, the best fruit fly is determined according to the enhanced non-dominance value. To guarantee the feasibility of the new solutions, an effective heuristic mechanism to handle constraints is adopted to repair the infeasible solutions. Meanwhile, an external archive is used to store the non-dominated solutions. The influence of parameter setting is investigated based on the Taguchi method of design of experiment, and a suitable parameter setting is suggested. Finally, numerical tests are carried out by using the IEEE 30-bus benchmark. The comparisons to some existing methods by using the technique for order preference by similarity to ideal solution (TOPSIS) demonstrate the effectiveness of the proposed algorithm.