关键词: 机器学习, 遗传算法, 模拟退火算法, 混合策略

Abstract: Combining advantages of Genetic Algorithm (GA) with Simulated Annealing (SA)algorithm, a new genetic annealing hybrid strategy, Modified Genetic Algorithm and Simulated Annealing(MGASA), was proposed. SA was regarded as the variation operator of GA population, which improved the local search ability and evolution. At the same time, the theory of machine-learning was introduced to MGASA, and so the average fitness of chromosomes was improved, the loss of the best solution was prevented and the speed of the evolution was increased. Then, the best solution could be obtained earlier. The simulation results of classic job-shop scheduling problems indicated the effectiveness of MGASA.

Key words: achine-learning, genetic algorithm, simulated annealing algorithm, hybrid strategy