摘要
针对作业车间调度问题,提出了最小化空闲时间的处理过程及其变异算子,设计了一种自适应遗传算法.该算法根据个体的特征确定交叉和变异次数,并根据种群特征不断修正种群.经典的调度基准问题测试表明:自适应措施能够有效保持种群的多样性,可以采用非常小的种群规模;最小化空闲时间的变异算子缩小了算法的搜索空间,大大提高了搜索效率.
For job-shop scheduling problem, a minimizing idle time process procedure and its mutation operator were put forward, and a self-adaptive genetic algorithm was designed. This algorithm get crossover and mutation times according to individuals＇ characters, and gradually correct the population according to current population＇ s property. Classic scheduling benchmark problem test shows ： the self-adaptive measure can efficiently keep current population ＇ s diversity, can use very small population size ; shortest idle time mutation operator reduces search space, greatly improves search efficiency.
出处
《鲁东大学学报（自然科学版）》
2007年第1期34-38,共5页
Journal of Ludong University:Natural Science Edition
