网站首页期刊简介编委会过刊目录投稿指南广告合作征订与发行联系我们English
冲压车间调度的动态拥挤度NSGA-II多目标优化方法
英文标题:Multiobject optimization method on stamping workshop scheduling based on dynamic congestion degree NSGAII algorithm
作者:刘世平 刘武发 
单位:河南职业技术学院 郑州大学 
关键词:冲压车间调度 多目标优化 动态拥挤度策略 NSGAII算法 Pareto前沿解集 
分类号:TH186
出版年,卷(期):页码:2021,46(1):76-82
摘要:

 为了降低冲压车间总能耗、缩短冲压件完成时间,提出了基于动态拥挤度NSGAII算法的冲压车间调度优化方法。分析了冲压机各工作状态,针对多制件、多工序调度问题,建立了以能耗最低、完成时间最短为优化目标的多目标优化模型。针对NSGAII算法中拥挤度比较算子会降低基因的多样性的问题,给出了动态拥挤度策略,该策略在删除多余染色体的同时,动态更新各染色体拥挤度,从而提出了基于动态拥挤度NSGAII算法的模型求解方法。经实例验证,NSGAII算法搜索的Pareto前沿解集不是真正的前沿解,而是陷入了局部最优,动态拥挤度NSGAII算法搜索出了Pareto前沿解集,其优化结果在能耗和完成时间上均优于NSGAII算法。

 In order to reduce energy consumption of stamping workshop and shorten producing time of stamping parts, the optimization method on stamping workshop scheduling based on dynamic congestion degree NSGA-II algorithm was proposed. Then, the different working states of stamping press were analyzed, and for the multi-part and multi-procedure scheduling problem, taking the lowest energy consumption and the shortest completion time as the optimization goal, the multi-object optimization model was built. Aiming at the fact that the congestion degree comparison operator in NSGA-II algorithm decreased the diversity of genes, a dynamic congestion degree strategy was given, which dynamically updated the congestion degree of each chromosome when the redundant chromosome was deleted so that the solving method based on dynamic congestion degree NSGA-II algorithm for the model was put forward. Instance verification shows that Pareto frontier solution set searched by NSGA-II algorithm is not real frontier solution, but falls into a local optimum. Thus, Pareto frontier solution set is searched by dynamic congestion degree NSGA-II algorithm, and its optimization results are better than the NSGA-II algorithm in terms of energy consumption and completion time.

基金项目:
基金项目:社会发展领域河南省科技攻关计划项目(142102310526)
作者简介:
作者简介:刘世平(1979-),男,硕士,讲师 E-mail:liushiping79@163.com 通讯作者:刘武发(1963-),男,博士,教授 E-mail:liuwufa63@163.com
参考文献:

 [1]熊玮,黄海鸿,朱利斌,等. 基于产品制造过程内含能分级的冲压车间节能调度研究[J].机械工程学报,2019,55(10):217-225.


Xiong W, Huang H H, Zhu L B, et al. Energysaving scheduling in stamping workshop based on ranks of product embodied energy during manufacturing[J]. Journal of Mechanical Engineering, 2019,55(10):217-225.

[2]Caglar Gencosman B, Begen M A, Ozmutlu H C, et al. Scheduling methods for efficient stamping operations at an automotive company[J]. Production & Operations Management, 2016, 25(11):1902-1918.

[3]王艳, 丁宇. 动态柔性作业车间优化调度与决策方法[J].系统仿真学报,2020,32(11):2073-2083.

Wang Y, Ding Y. ACO integrated approach for solving flexible jobshop scheduling with multiple process plans [J]. Journal of System Simulation, 2020, 32(11):2073-2083.

[4]黄学文, 张晓彤, 艾亚晴. 基于蚁群算法的多加工路线柔性车间调度问题[J]. 计算机集成制造系统, 2018,24(3):558-569.

Huang X W, Zhang X T, Ai Y Q. ACO integrated approach for solving flexible jobshop scheduling with multiple process plans [J]. Computer Integrated Manufacturing Systems, 2018,24(3):558-569.

[5]秦军, 睢鹏,李昌玲,等. 基于多智能体共享认知的车间动态调度方法研究[J]. 制造技术与机床,2020,(1):161-168.

Qin J, Sui P, Li C L, et al. Research on dynamic workshop scheduling based on multiagent shared ognition [J]. Manufacturing Technology & Machine Tool, 2020,(1):161-168.

[6]周春生. 面向节能的冲压车间分批调度研究[D]. 合肥:合肥工业大学,2018.

Zhou C S. Study on Energysaving and Batch Scheduling in Pressing Jobshop [D]. Hefei: Hefei University of Technology, 2018.

[7]朱先萌, 姜兆亮, 魏清月, 等. 多品种小批量产品冲压计划排程多目标优化[J]. 计算机集成制造系统, 2017,23(9):78-87.

Zhu X M, Jiang Z L, Wei Q Y, et al. Multiobjective optimization for stamping plan scheduling of multivarieties and smallbatch products [J]. Computer Integrated Manufacturing Systems, 2017,23(9):78-87.

[8]刘鑫平, 顾春华,罗飞,等. 基于败者组与混合编码策略的NSGAII改进算法[J]. 计算机科学,2019,46(10):222-228.

Liu X P, Gu C H, Luo F, et al. Improved NSGAII algorithm based on loser group and hybrid coding strategy [J]. Computer Science, 2019,46(10):222-228.

[9]Gustavsson P, Syberfeldt A. A new algorithm using the nondominated tree to improve nondominated sorting[J]. Evolutionary Computation, 2018, 26(1):89-116.

[10]樊田田, 许蕾,陈林. 基于多目标优化算法NSGAII推荐相似缺陷报告[J]. 计算机学报,2019,42(10):2175-2189.

Fan T T, Xu L, Chen L. Recommending similar bug reports based on multitargets optimization algorithm NSGAII [J]. Chinese Journal of Computers, 2019,42(10):2175-2189.

[11]巩玲君, 张纪海. 基于NSGAII的应急生产任务多目标优化模型及算法研究[J]. 运筹与管理, 2019,28(12):7-13.

Gong L J, Zhang J H. Multiobjective emergency production assignment model based on NSGAII [J]. Operations Research and Management Science, 2019,28(12):7-13.

[12]张超勇, 饶运清,刘向军,等. 基于POX交叉的遗传算法求解JobShop调度问题[J]. 中国机械工程,2004, 15(23):2149-2153.

Zhang C Y, Rao Y Q, Liu X J, et al. An improved genetic algorithm for the job shop scheduling problem [J]. China Mechanical Engineering, 2004, 15(23):2149-2153.
服务与反馈:
本网站尚未开通全文下载服务】【加入收藏
《锻压技术》编辑部版权所有

中国机械工业联合会主管 北京机电研究所有限公司 中国机械工程学会塑性工程分会主办
联系地址:北京市海淀区学清路18号 邮编:100083
电话:+86-010-82415085 传真:+86-010-62920652
E-mail: fst@263.net(稿件) dyjsjournal@163.com(广告)
京ICP备07007000号-9