考虑机器能耗的绿色作业车间调度问题  

Green Job Shop Scheduling Problem Considering Machine Energy Consumption

作　　者：吕海利 孙佳祺[1] 吴姝 LU Hai-li;SUN Jia-qi;WU Shu(Institute of Logistics System Science and Engineering,School of Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China;Engineering Research Center of Ministry of Education for Port Logistics Technology and Equipment,Wuhan University of Technology,Wuhan 430063,China)

机构地区：[1]武汉理工大学物流工程学院物流系统科学与工程研究所,湖北武汉430063 [2]武汉理工大学港口物流技术与装备教育部工程研究中心,湖北武汉430063

出　　处：《运筹与管理》2021年第12期220-225,共6页Operations Research and Management Science

基　　金：国家自然科学基金青年科学基金项目(11701437);武汉理工大学自主创新研究基金项目(195218008)。

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。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.

关 键 词：绿色作业车间调度 关机/重启 局部调整 遗传算法 

分 类 号：TH18[机械工程—机械制造及自动化]