%0 Journal Article %A Panpan Xu and Shulin Sui and Zongjie Du %D 2015 %J International Journal of Mathematical and Computational Sciences %B World Academy of Science, Engineering and Technology %I Open Science Index 107, 2015 %T Application of Hybrid Genetic Algorithm Based on Simulated Annealing in Function Optimization %U https://publications.waset.org/pdf/10003238 %V 107 %X Genetic algorithm is widely used in optimization problems for its excellent global search capabilities and highly parallel processing capabilities; but, it converges prematurely and has a poor local optimization capability in actual operation. Simulated annealing algorithm can avoid the search process falling into local optimum. A hybrid genetic algorithm based on simulated annealing is designed by combining the advantages of genetic algorithm and simulated annealing algorithm. The numerical experiment represents the hybrid genetic algorithm can be applied to solve the function optimization problems efficiently. %P 695 - 698