Abstract: For the traditional job shop scheduling problem (JSP), on the premise of guaranteeing the due date, the green shop scheduling problem (GSSP) with strategy of turning off and on is studied. The objective is to minimize machine energy consumption. A mathematical programming model is established. Then, under the framework of genetic algorithm, a local adjustment decoding method is proposed according to the characteristics of the problem. This decoding method moves the operations during schedule generation and determines the start time of the process. Finally, a small-scale numerical example is given to verify the validity of the decoding. The genetic algorithm based on local adjustment decoding and sequential decoding is compared and tested by multiple sets of examples. The results show that the proposed local adjustment decoding can reduce the energy consumption of the machine and improve the efficiency of the solution.

Key words: green job shop scheduling problem, turning off and on strategy, local adjustment, genetic algorithm

摘要： 针对传统作业车间调度,在保证交货期的前提下,以机器能耗最小为目标研究带有关机/重启策略的绿色车间调度问题。首先建立数学规划模型,然后在遗传算法的框架下,根据问题特点提出了一种局部调整的解码方式,在排产时进行工序的移动并确定其开始加工时刻。最后进行小规模算例运算,验证数学规划模型的有效性,再利用算例对基于局部调整解码和顺序解码的遗传算法进行对比测试,结果表明提出的局部调整解码可以在降低机器能耗的同时提高求解效率。

关键词: 绿色作业车间调度, 关机/重启, 局部调整, 遗传算法