【摘要】 利用遗传算法(GA)和模拟退火算法(SA)求解该问题近优解的有效性和实用性,提出一种实现车间调度的混合遗传算法(GASA),给出了一个新的编码方法,并建立了相应编码的解码规则。对初始温度的确定方法和获得适应度函数的方法进行了探讨。基于LA16调度问题,分别利用该方法和单纯遗传算法及模拟退火算法进行了模拟仿真计算,计算结果表明该混合算法克服了单纯遗传算法和模拟退火算法在车间调度优化方面的不足,具有较高的鲁棒性。更多还原

【Abstract】 Based on the good characteristics of genetic algorithm(GA) and simulated annealing(SA) in achieving near optional solution of this problem, a hybrid algorithm of genetic and annealing(GASA) was proposed for the solution of job shop scheduling, and a new encoding method was presented for this hybrid algorithm, the corresponding decode method was established also. Meanwhile, the methods of getting the initial temperature and the fitness function were discussed. The simulation of the LA16 scheduling problem shows the feasibilities and availabilities of GAGA, and the simulated results based on GASA、SA and GA show that this hybrid genetic algorithm has higher robustness and can improve on the deficiencies of genetic algorithm and simulated annealing in the optimization on JSSP.更多还原