Abstract: The hill-climbing method is a local search algorithm，which has a good local search performance mainly because its search process is guided by information between individuals.In contrast，Traditional Genetic Algorithm（TGA） is a global search algorithm，which does not consider information between individuals in the search process.The convergence of TGA is limited because it only uses individuals’ fitness to guide the search.This paper proposes a new algorithm in which oriented hill-climbing mechanism is added to genetic algorithm.The new algorithm is named Oriented Hill-Climbing based Genetic Algorithm（OHCGA） which combines merits of hill-climbing method and TGA.Through the comparison of individuals，the algorithm uses the oriented hill-climbing operator to guide search to promising areas.Numerical experiments show that OHCGA improves the convergence speed and the ability of search optimal solutions compared with TGA.