Multi-objective optimization in the presence of ramp-rate limits using non-dominated sorting hybrid fruit fly algorithm

A novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, total power losses and voltage stability index as objectives. Fruit fly Algorithm (FFA) along with real coded Genetic Algorithm (GA) cross-over operation treated as Hybrid Fruit fly Algorithm (HFFA) is proposed to select best value as compared with existing single-objective evaluation algorithms and the proposed non-dominated sorting hybrid fruit fly algorithm (NSHFFA) is used for the multi-objective optimal power flow problem. A fuzzy decision making tool is used to select the best Pareto front from the total generated solutions by the proposed algorithm. The effectiveness of the proposed algorithm is analyzed for various standard test systems such as Booth’s function, Schaffer 2 function and IEEE 30 bus system. The obtained results using proposed algorithm are compared with the existing optimization methods. The results reveal better solution and computational efficiency of the proposed algorithm.