30 International Journal of Applied Evolutionary Computation, 5(1), 30-51, January-March 2014 Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. ABSTRACT In this research, a study was carried out to exploit the hybrid schemes combining two classical local search techniques i.e. Nelder–Mead simplex search method and bidirectional random optimization with two meta- heuristic methods i.e. the shuffed frog leaping and the shuffed complex evolution, respectively. In this hybrid methodology, each subset of meta-heuristic algorithms is improved by a hybrid strategy that is combined from evolutionary process of each subset in related algorithm and a local search method. These hybrid algorithms are evaluated on low and high dimensional continuous benchmark functions and the obtained results are com- pared with their non-hybrid competitors. The obtained results demonstrate that the hybrid algorithm combined from shuffed frog leaping and Nelder–Mead simplex has a better success rate but a higher number of function evaluations on low-dimensional functions than the shuffed frog leaping. Whereas on high-dimensional func- tions it has a better success rate and a faster performance. Also the hybrid algorithm combined from shuffed complex evolution and bidirectional random optimization obtains a better performance in terms of success rate and function evaluations than shuffed complex evolution on low dimensional functions; whereas on high-dimensional functions, it obtains a better success rate but a slower performance. Also a comparison of our hybrid algorithms with the other evolutionary algorithms reported in the literature confrms our proposed algorithms have the best performance among all compared algorithms. Hybridizing Shuffed Frog Leaping and Shuffed Complex Evolution Algorithms Using Local Search Methods Morteza Alinia Ahandani, Department of Electrical Engineering, Young Researchers Club, Islamic Azad University, Langaroud Branch, Langaroud, Iran Hosein Alavi-Rad, Department of Electrical Engineering, Young Researchers Club, Islamic Azad University, Langaroud Branch, Langaroud, Iran Keywords: Bidirectional Random Optimization, Hybrid Algorithms, Nelder–Mead Simplex Search, Shuffed Complex Evolution, Shuffed Frog Leaping INTRODUCTION Two of the recent algorithms in the class of stochastic search methods and evolutionary algorithms (EAs) are shuffled complex evolu- tion (SCE) (Duan et al., 1992) and shuffled frog leaping (SFL) (Eusuff & Lansey, 2003). These algorithms are two stochastic optimization methods which use partitioning and shuffling processes. Partitioning and shuffling processes by sharing past experiments of each member with other members, help to improve the DOI: 10.4018/ijaec.2014010103