A novel Hybrid FFA-ACO Algorithm for Economic Power Dispatch

Abstract

In this article, I developed a practical combination strategy for two evolutionary algorithms; a firefly algorithm and Ant Colony Optimization (FFA- ACO) which inherited the superiority of the two
algorithms for solving the economic power dispatch (EPD) problem. ACO has strong and easy to
combine with other methods in optimization and the FFA algorithm has a very great ability to search
solutions with a fast speed to converge, contrary to the most meta-heuristic algorithms. The hybrid
approach involves two level of optimization, namely global search by the ACO and local search by the
FFA, which cooperates in a global process of optimization. It can provide more robust convergence. This
method was tested on the modified IEEE 30 bus test system. The outcomes are compared with many
other methods like swarm optimization (PSO), Tabu Search (TS), improved evolutionary programming
(IEP), differential evolution (DE), evolutionary programming (EP) and non-linear programming (NLP).
The proposed method is found to be computationally faster, robust and superior