基于群集一致性的生产—物流资源实时协同调度方法

doi:10.13196/j.cims.2022.09.025

计算机集成制造系统 ›› 2022, Vol. 28 ›› Issue (9): 2953-2969.DOI: 10.13196/j.cims.2022.09.025

基于群集一致性的生产—物流资源实时协同调度方法

李文锋¹,杨文超^1,2,罗国富²

1.武汉理工大学交通与物流工程学院
2.郑州轻工业大学机电工程学院

出版日期:2022-09-30 发布日期:2022-10-09
基金资助:
国家自然科学基金资助项目(62173263,61571336)。

Real-time collaborative scheduling method of production-logistics resources based on swarm consistency

LI Wenfeng¹,YANG Wenchao^1,2,LUO Guofu²

1.School of Transportation and Logistics Engineering,Wuhan University of Technology
2.School of Mechanical and Electrical Engineering,Zhengzhou University of Light Industry

Online:2022-09-30 Published:2022-10-09
Supported by:
Project supported by the National Natural Science Foundation,China(No.62173263,61571336).

摘要/Abstract

摘要： 近年来,客户个性化需求给企业带来了小批量、多样化的随机订单,产生了一类工件到达时间随机的作业车间调度问题,对企业竞争力造成重要影响。这种动态调度需求对如何协同调度车间内的生产和物流资源形成了挑战。针对这一问题,引入群集技术,构建了群集生产—物流资源任务一致性模型,根据个性化订单特征构建了基于实时信息的任务松弛度模型,提出一种考虑生产—物流资源一致性的实时调度方法,实现了智能作业车间面向随机订单到达的群集资源实时自适应协同。结合仿真案例,对所提方法的有效性进行了评估。实验结果表明,所提算法优于3种对比算法,具有更好的鲁棒性,并可以有效克服实时调度方法“短视”的不足。

关键词: 生产—物流资源, 群集, 一致性, 资源协同, 实时调度

Abstract: In recent years,the individualized demand of customers brings small batches and diversification of orders towards enterprises,which brings a new type of the job shop scheduling problem and has a fundamental and practical significance onthe competitiveness of an enterprise.Collaborative schedule of production and logistics resources on a shop floor is very challenging to meet this dynamical scheduling requirement.To solve the problem,a task consistency model of production-logistics resources based on swarm technology was constructed,the slack task model was built according to personalized orders and real-time workshop information characteristics,and then a production logistics real-time scheduling method considering the task consistency between production and logistics was proposed to realize the real-time adaptive collaboration of swarm resources in an intelligent job shop for random order arrival.The proposed algorithm was carried out with several simulation cases to evaluate its effectiveness.Experimental results showed that the proposed algorithm was superior to three existing algorithms.The proposed method had better robustness and could effectively overcome the shortage of “shortsightedness” of real-time scheduling methods.

Key words: production-logistics resources, swarm, consistency, resource coordination, real-time scheduling

中图分类号:

李文锋, 杨文超, 罗国富. 基于群集一致性的生产—物流资源实时协同调度方法[J]. 计算机集成制造系统, 2022, 28(9): 2953-2969.

LI Wenfeng, YANG Wenchao, LUO Guofu. Real-time collaborative scheduling method of production-logistics resources based on swarm consistency[J]. Computer Integrated Manufacturing System, 2022, 28(9): 2953-2969.

[1]	孙阳君, 赵宁. 多机器人存取系统动态调度方法[J]. 计算机集成制造系统, 2022, 28(7): 2213-2228.
[2]	孙阳君,赵宁. 基于数字孪生的多自动导引小车系统集中式调度[J]. 计算机集成制造系统, 2021, 27(2): 569-584.
[3]	任剑,谢翠华,杨艺,卞灿. 智能工厂建设方案的正态云多准则优选方法[J]. 计算机集成制造系统, 2021, 27(10): 2990-3003.
[4]	刘睿,尹旭悦,范秀敏,王磊,何其昌. 面向AR辅助引导的线缆敷设质量一致性视觉检测方法[J]. 计算机集成制造系统, 2021, 27(1): 54-63.
[5]	林志炳. 考虑随机参照价格的供应链定价策略[J]. 计算机集成制造系统, 2020, 26(第4): 1072-1080.
[6]	陈振颂,王先甲,王欣仪,常建鹏. 基于PD-HFLTS与BWM的多产品可持续供应商选择[J]. 计算机集成制造系统, 2020, 26(第2): 508-521.
[7]	王颖,周晓宇,王钊,张学馨,陈丽娇. 基于Artifact生命周期的业务流程一致性检查[J]. 计算机集成制造系统, 2019, 25(第4): 856-863.
[8]	滕苑秀,杜玉越,王路. 循环并发结构的过程模型修正方法[J]. 计算机集成制造系统, 2019, 25(第4): 882-893.
[9]	笪建,莫启,程耀坤,张毅,李彤. 业务协同中组织需求的建模与一致性验证[J]. 计算机集成制造系统, 2018, 24(第9): 2186-2200.
[10]	莫启,代飞,朱锐,笪建,郑明,李彤,林雷蕾,戴翼超. 参与组织需求与协同业务过程一致性验证方法[J]. 计算机集成制造系统, 2018, 24(第7): 1608-1620.
[11]	牟能冶,常建鹏,陈振颂. 基于PD-HFLTS与群决策理论的可持续供应商选择[J]. 计算机集成制造系统, 2018, 24(第5): 1261-1278.
[12]	邓昌义,郭锐锋,吴昊天,彭阿珍,杜少华,盖荣丽. 基于滑动窗口的低能耗高可靠调度算法[J]. 计算机集成制造系统, 2018, 24(第10): 2395-2406.
[13]	刘进,郭立鹏,雷建坤,张亮. 业务流程即服务中的数据映射问题研究[J]. 计算机集成制造系统, 2017, 23(第5期): 1000-1006.
[14]	许荣斌,刘鑫,杨壮壮,郭星,谢莹,吴建国. 基于任务执行截止期限的有向无环图实时调度方法[J]. 计算机集成制造系统, 2016, 22(第2期): 455-464.
[15]	袁际军,黄敏镁. 非二元条件约束满足问题求解[J]. 计算机集成制造系统, 2014, 20(3): 636-.

基于群集一致性的生产—物流资源实时协同调度方法

Real-time collaborative scheduling method of production-logistics resources based on swarm consistency

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics