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针对双资源约束作业车间调度的双目标优化问题,提出一种继承式遗传算法,通过分支种群继承父辈种群的进化经验.该算法面向双资源约束特点,采用4维染色体编码方式,基于时间窗口比较实现活动化调度,通过资源进化算子提高算法全局搜索能力;基于个体Pareto指数的锦标赛选择策略,有效削弱了染色体Pareto排序级别对个体存活概率的影响以保持群体多样性,并利用精英保留策略提高了解的收敛性.仿真实验与分析结果表明了所提算法具有优良性能.
In order to solve the bi-objective optimization problem of dual resource constrained job shop scheduling, an inherited genetic algorithm is proposed to inherit the evolutionary experience of the parental population through the branch population. The algorithm uses four-dimensional chromosome encoding and compares the time window The scheduling algorithm based on Pareto index can effectively reduce the effect of Pareto ranking on individual survival probability in order to maintain the population diversity and utilize the elite retention strategy to improve the global search ability of the algorithm through resource evolution operator. The convergence of the proposed algorithm is verified by simulation and analysis. The results show that the proposed algorithm has good performance.