分时电价下基于NSGA-Ⅱ的柔性作业车间绿色调度  

Green Scheduling of Flexible Job Shops Based on NSGA-Ⅱunder TOU Power Price

作　　者：刘彩洁 徐志涛 张钦[1] 张力菠[1] 姚坤 LIU Caijie;XU Zhitao;ZHANG Qin;ZHANG Libo;YAO Kun(College of Economics and Management,Nanjing University of Aeronautics and Astronautics,Nanjing,211106)

机构地区：[1]南京航空航天大学经济与管理学院,南京211106

出　　处：《中国机械工程》2020年第5期576-585,共10页China Mechanical Engineering

基　　金：国家自然科学基金资助项目(71774081,71702073);江苏省自然科学基金资助项目(BK20170774);中国博士后科学基金资助项目(2018M640483);浙江省博士后科学基金资助项目(zj20180024);南京航空航天大学基本科研业务费资助项目(NP2017305)。

摘　　要：通过规划绿色生产调度实现了时间、经济和能耗三者的协同优化。以柔性作业车间为背景,结合分时电价政策,构建了设备不同工作状态下的设备能耗成本计算模型;同时兼顾碳排放与订单交付等绿色生产车间管理要求,建立了包括最小化碳排放、能耗成本和最大完工时间在内的柔性作业车间绿色调度多目标优化模型;为避免算法过早陷入“早熟”并保持种群多样性,采用基于动态控制参数和改进精英保留策略的快速非支配排序遗传算法(NSGA-Ⅱ)进行求解;最后,通过具体算例验证了所建立模型的可行性与改进算法的优越性。The coordinated optimization of time,economic and energy consumption was realized by planning the green production scheduling.Considering the TOU price policy of the electricity,the energy cost models under different production conditions were established based on the flexible job shop.Incorporating the green production shops management requirements,such as carbon emissions and order delivery,a green scheduling multi-objective optimization model was formulated to minimize carbon emissions,energy costs and makespan.In order to avoid the premature convergence of algorithm and maintain the diversity of population,the non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)with dynamic control parameter and improved elite retention strategy was proposed to solve this problem.Finally,the feasibility of the model and the superiority of the improved algorithm were verified by a real-world case.

关 键 词：柔性作业车间 分时电价 多目标 调度优化 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]