面向韧性提升的可重入车间绿色调度与预维护协同优化*

doi:10.16731/j.cnki.1671-3133.2026.07.003

现代制造工程 ›› 2026, Vol. 550 ›› Issue (7): 19-32.doi: 10.16731/j.cnki.1671-3133.2026.07.003

• 先进制造系统管理运作 • 上一篇下一篇

面向韧性提升的可重入车间绿色调度与预维护协同优化^*

董君^1,2, 叶春明³

1 河南工学院管理学院,新乡 453003;
2 新乡市数字化工厂规划工程技术研究中心,新乡 453003;
3 上海理工大学管理学院,上海 200093

收稿日期:2025-05-22 出版日期:2026-07-18 发布日期:2026-08-05
作者简介:董君,副教授,博士,主要研究方向为调度优化、智能算法。E-mail:dj8519@163.com
基金资助:
^*国家社会科学基金后期资助项目(22FGLB109);河南省软科学研究计划项目(252400410617);河南工学院高层次人才科研启动项目(KQ2106)

Collaborative optimization of reentrant workshop green scheduling and preventive maintenance for resilience enhancement

DONG Jun^1,2, YE Chunming³

1 Business School,Henan Institute of Technology,Xinxiang 453003,China;
2 Xinxiang Digital Factory Planning Engineering Technology Research Center,Xinxiang 453003,China;
3 Business School,University of Shanghai for Science & Technology,Shanghai 200093,China

Received:2025-05-22 Online:2026-07-18 Published:2026-08-05

摘要/Abstract

摘要： 在经济全球化加速推进的背景下,制造企业面临着许多诸如供应链中断、自然灾害及客户个性化需求等外部冲击和挑战,可能会对企业生产运作管理造成严重影响。针对制造企业韧性的提升问题,设计多源供能背景下考虑分时电价和客户侧订单紧急程度的需求响应协同优化策略,实现绿色调度与设备预维护的协同优化及低平谷时段生产负荷的转移,有效提升系统能源供给及生产运作的韧性。提出改进的鲸鱼群算法,通过开发“最近较优个体”寻优策略、个体间移动策略及个体扰动策略,有效地挖掘种群新的搜索空间,避免算法陷入局部最优,提升算法寻优性能。最后通过实验对比分析,验证该算法求解的有效性和竞争优势。

关键词: 韧性提升, 生产调度与预维护, 需求响应协同优化, 鲸鱼群算法

Abstract: Against the backdrop of accelerated economic globalization,manufacturing enterprises face many external shocks and challenges such as supply chain disruptions,natural disasters,and personalized customer demands,which may have a serious impact on the production and operation management. To address the manufacturing enterprises resilience enhancement problem,a demand response driven mechanism considering time of use electricity prices and customer order urgency under the background of multi-source energy supply is designed to achieve collaborative optimization of production scheduling and equipment preventive maintenance,as well as transfer of production load during low peak and valley periods,and effectively improve the resilience of system energy supply and production operations. An improved whale swarm algorithm is proposed,which effectively explores new search spaces in the population by developing optimization strategies for ″nearest best individual″, inter-individual movement strategies,and individual perturbation strategies,which avoid the algorithm from getting stuck in local optima and improve its optimization performance. Finally,through experimental comparative analysis,the algorithm effectiveness and competitive advantage are verified.

Key words: resilience enhancement, production scheduling and preventive maintenance, demand response collaborative optimization, whale swarm algorithm

中图分类号:

TP18

董君, 叶春明. 面向韧性提升的可重入车间绿色调度与预维护协同优化^*[J]. 现代制造工程, 2026, 550(7): 19-32.

DONG Jun, YE Chunming. Collaborative optimization of reentrant workshop green scheduling and preventive maintenance for resilience enhancement[J]. Modern Manufacturing Engineering, 2026, 550(7): 19-32.

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面向韧性提升的可重入车间绿色调度与预维护协同优化^*

Collaborative optimization of reentrant workshop green scheduling and preventive maintenance for resilience enhancement

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