Production-Logistics Synchronized Scheduling in Matrix Cellular Manufacturing Systems Employing Multi-Scenario Multi-Objective Robust Optimization

LI Mingxing; XU Jianan; GUO Daqiang; ZHONG Runyang; QU Ting

doi:10.7652/xjtuxb202608016

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Production-Logistics Synchronized Scheduling in Matrix Cellular Manufacturing Systems Employing Multi-Scenario Multi-Objective Robust Optimization

更新时间：2026-07-28

- Production-Logistics Synchronized Scheduling in Matrix Cellular Manufacturing Systems Employing Multi-Scenario Multi-Objective Robust Optimization
- Journal of Xi'an Jiaotong University Vol. 60, Issue 8, Pages: 181-192(2026)
- 作者机构：
  
  暨南大学智能科学与工程学院，519070，广东珠海
  暨南大学广东省大湾区智慧物流国际科技合作基地，519070，广东珠海
  暨南大学物联网与物流工程研究院，519070，广东珠海
  香港科技大学（广州）系统枢纽智能制造学域，511453，广州
  香港大学数据与系统工程系，999077，香港
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202608016
  CLC： TH168
- Received：01 March 2026，
  
  Online First：10 April 2026，
  
  Published：10 August 2026
- 稿件说明：
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LI Mingxing, XU Jianan, GUO Daqiang, et al. Production-Logistics Synchronized Scheduling in Matrix Cellular Manufacturing Systems Employing Multi-Scenario Multi-Objective Robust Optimization[J]. Journal of Xi'an Jiaotong University, 2026, 60(8): 181-192.
DOI：

LI Mingxing, XU Jianan, GUO Daqiang, et al. Production-Logistics Synchronized Scheduling in Matrix Cellular Manufacturing Systems Employing Multi-Scenario Multi-Objective Robust Optimization[J]. Journal of Xi'an Jiaotong University, 2026, 60(8): 181-192. DOI： 10.7652/xjtuxb202608016.

摘要

针对矩阵式单元制造系统生产-物流联动调度中时空耦合关系复杂，以及设备故障、作业时间波动等不确定性扰动频发的问题，提出了一种多场景多目标鲁棒优化调度模型。首先，采用场景表示法刻画多源不确定性，构建了以最小化订单同步时间、生产-物流同步时间及最大完工时间的多目标鲁棒优化模型。其次，设计了基于多场景鲁棒优化的模拟退火算法（MRSA），结合自适应权重调整机制，动态平滑多目标间的量纲差异，通过监测种群在各目标维度上的归一化偏离度，实现对解空间的高效均衡搜索。不同规模的算例仿真实验表明：在低、中、高不确定性场景下，所提鲁棒调度模型相比标称确定性模型，其最大完工时间等核心指标的抗风险底线（CVaR）实现了45%以上的优化；相较于固定权重模拟退火算法（FW-MSA）

MRSA算法在关键性能指标上实现了20%～40%的显著优化。研究结果证实了所提模型与自适应算法实现了生产效率与风险控制的双重优化。

Abstract

To address the complex spatio-temporal coupling relations and frequent multi-source uncertainties (e.g.

equipment failures and processing time fluctuations) in the production-logistics synchronized scheduling of matrix cellular manufacturing systems

a multi-scenario multi-objective robust optimization approach was proposed. First

a scenario-based method was employed to characterize multi-source uncertainties

and a multi-objective robust optimization model was developed to minimize the order synchronization time

production-logistics synchronization time

and makespan. Second

a multi-scenario robust simulated annealing (MRSA) algorithm was designed

incorporating a self-adaptive weight adjustment mechanism to dynamically smooth dimensional differences among multiple objectives. By monitoring the normalized deviation of the population in each objective dimension

the algorithm achieves an efficient and balanced search of the solution space. Simulation experiments across various problem scales demonstrate that

compared to the nominal deterministic model

the proposed robust scheduling model improves the conditional value at risk (CVaR) of core indicators (e.g.

makespan) by over 45% under low

medium

and high uncertainty scenarios. Furthermore

compared to the fixed-weight multi-scenario simulated annealing (FW-MSA) algorithm

MRSA achieves a significant 20%—40% improvement in key performance indicators (KPIs) .The results confirm that the proposed model and self-adaptive algorithm effectively optimize both production efficiency and risk mitigation.

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