基于DNA遗传算法求解机床加工调度问题

研究了机床加工的多目标调度问题,提出一种基于DNA计算的混合遗传算法,结合Pareto非支配排序法来求解。为保证最优解集的多样性,采用四进制编码方式,将DNA序列分成中性和有害两部分,交叉操作只在中性部分进行;由动态变化的变异概率决定是否执行变异操作,并比较设计的算法与常规遗传算法获得的结果。试验结果表明,可以有效地解决机床加工中的多目标调度问题。

Resolve Machine Tool Scheduling Problems Based on DNA Genetic Algorithm

Studied on the multi-objective scheduling problem of machine tool,proposed a hybrid genetic algorithm based on DNA computing,combined it with Pareto non-dominated sorting to resolve multi-objective flexible scheduling problems.In order to ensure the diversities of the optimal solution sets,adopt quaternary encoding,divide the DNA sequences which obtained by using the Elitism strategy into two parts：neutral part and harmful part,the crossover operation will only been performed in the neutral part;the implementation of mutation depends on the dynamic mutation probability,compare the results obtained by the designed algorithms and standard genetic algorithm,Testes show that the algorithm can effectively solve the multi-objective scheduling problem of machine tool.