Hybrid Mean-Variance Mapping Optimization for solving the IEEE-CEC 2013 competition problems

Mean-Variance Mapping Optimization (MVMO) is a recent addition to the emerging field of heuristic optimization algorithms, which has been quite successful in solving a variety of power system optimization problems. This paper introduces a hybrid variant of MVMO (MVMO-SH) for solving the IEEECEC 2013 competition test suite. MVMO-SH is based on a swarm scheme of MVMO with embedded local search and multi-parent crossover strategies to increase search diversity and solution quality. Numerical results attest to the promising prospect of MVMO-SH to become a general purpose optimization algorithm.