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求解作业车间调度问题的一种自适应遗传算法
A Self-adaptive Genetic Algorithm for Job-shop Scheduling
【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.
【Abstract】 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.
【Key words】 job-shop scheduling problem; self-adaptive genetic algorithm; shortest idle time;
- 【文献出处】 鲁东大学学报(自然科学版) ,Ludong University Journal(Natural Science Edition) , 编辑部邮箱 ,2007年01期
- 【分类号】TP18
- 【被引频次】5
- 【下载频次】192