Computers & Industrial Engineering最新文献

Harmonizing sustainability and resiliency: A novel robust-stochastic decomposition approach for effective mask distribution and recycling 协调可持续性和弹性：一种新的鲁棒随机分解方法，用于有效的面罩分配和回收

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-28 DOI: 10.1016/j.cie.2026.111837

Mahsa Mohammadi , Babak Mohamadpour Tosarkani

This study aims to develop a novel graph theory-based clustering algorithm for large-scale logistics planning problems focusing on the distribution of face masks by various transportation modes under uncertainty. A robust multi-objective, mixed-integer linear programming model (MILPM) is utilized to handle imprecise parameters (e.g., demand and processing time). The proposed model supports decision-makers in designing a sustainable closed-loop supply chain network for the optimal face mask distribution under time window limitations. A sample average approximation methodology is applied to tackle the large-scale case study. Furthermore, a graph theory-based clustering algorithm is proposed to accelerate the scenario decomposition approach since it deals with less scenarios in comparison with sample average approximation and scenario decomposition. Silhouette analysis is conducted to measure the performance and accuracy of the generated clusters. Sensitivity analyses are implemented to validate the efficiency and applicability of the presented solution approach. A series of scenarios is set to represent supply chain network disruptions with unknown probabilities. The outcome of this study denotes the optimal flow of face masks and the optimum number of facilities at the time of the COVID-19 outbreak in Toronto, Canada.

针对不确定条件下不同运输方式口罩分配的大规模物流规划问题，提出一种新的基于图论的聚类算法。利用鲁棒多目标混合整数线性规划模型（MILPM）处理不精确参数（如需求和加工时间）。该模型支持决策者在时间窗口限制下设计可持续的闭环供应链网络，以实现口罩的最优分配。采用样本平均近似方法处理大规模案例研究。此外，提出了一种基于图论的聚类算法，与样本平均近似和场景分解相比，它处理的场景更少，从而加快了场景分解的速度。通过剪影分析来衡量生成的聚类的性能和准确性。通过灵敏度分析验证了所提出的求解方法的有效性和适用性。一系列场景被设置为代表未知概率的供应链网络中断。这项研究的结果表明，在加拿大多伦多发生COVID-19疫情时，口罩的最佳流量和设施的最佳数量。

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引用次数: 0

Optimal control policy for combined production–maintenance and multivariate quality monitoring of an imperfect manufacturing system with replenishment and assignable causes 具有补货和可分配原因的不完善制造系统的生产维护和多变量质量监控的最优控制策略

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-28 DOI: 10.1016/j.cie.2026.111871

Qiang Wan , Yanni An , Mei Zhu

Current research that integrates the three functions of production planning, maintenance, and quality monitoring suffers from three significant shortcomings: (1) Assume that there is only one identifiable source of variation within the process. Due to the inherent complexity characteristic of most real-world manufacturing operations, the simplified assumption of a single assignable cause is seldom observed in actual industrial settings. When the actual assignable cause of a process shift does not match the one anticipated in quality monitoring, performance may be subpar in both economic and statistical terms. (2) Monitoring a single quality characteristic, however, in actual conditions, multiple process quality characteristics should be monitored simultaneously. (3) To simplify the model, the buffer inventory time is established at the start of the cycle. However, if the buffer is loaded too early, it may result in excess inventory holding expenses. To handle these shortcomings, this work establishes an integration scheme for production, multivariate statistical process monitoring and maintenance planning that considers dynamical replenishment and multiple assignable causes. Under economic–statistical quality constraints, a customized genetic algorithm is employed to optimize the expected total cost of each process cycle. In the comparative study, the proposed model is compared with integrated models using a single assignable cause, MEWMA, and MCUSUM charts, highlighting its superior economic and statistical performance. Finally, a design of experiments (DOE)-based sensitivity analysis is carried out on the principal process parameters and the average total cost per cycle.

目前将生产计划、维护和质量监控三个功能集成在一起的研究存在三个显著缺陷：(1)假设过程中只有一个可识别的变异源。由于大多数现实世界制造操作的固有复杂性，在实际工业环境中很少观察到单一可分配原因的简化假设。当过程转移的实际可分配原因与质量监控中预期的原因不匹配时，从经济和统计角度来看，绩效可能低于标准。(2)监测单一质量特征，但在实际条件下，应同时监测多个过程质量特征。(3)为了简化模型，在周期开始时建立缓冲库存时间。但是，如果缓冲区加载得太早，可能会导致库存持有费用过多。为了解决这些问题，本文建立了一个生产、多元统计过程监控和维修计划的集成方案，该方案考虑了动态补货和多种可分配原因。在经济统计质量约束下，采用自定义遗传算法对各工序周期的期望总成本进行优化。在比较研究中，将所提出的模型与使用单一可分配原因、MEWMA和mccusum图表的综合模型进行了比较，突出了其优越的经济和统计性能。最后，对主要工艺参数和每周期平均总成本进行了基于试验设计（DOE）的灵敏度分析。

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引用次数: 0

Joint optimization of vending machine deployment and shelf display design with synchronized merchandise replenishment 联合优化自动售货机部署和货架展示设计，同步商品补充

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-25 DOI: 10.1016/j.cie.2026.111848

Kung-Jeng Wang , Natalia Febri

Vending machines (VMs) serve as an important aspect of automated retail, delivering both flexibility in operations and convenience for consumers. However, as VM networks expand, managers face growing logistical challenges in determining optimal deployment locations, product selection and allocation, and restocking schedules. This study proposes a novel bi-layer optimization framework that jointly optimizes deployment, product selection and allocation, and a synchronized replenishment cycle. To address the complexity of this large-scale combinatorial problem, we develop a hybrid Tabu Search and Evolution Strategy (TS-ES) algorithm. Extensive experiments show that the synchronized replenishment cycle yields better performance than the independent cycle. Comparative analysis demonstrates that the hybrid TS-ES algorithm consistently achieves higher objective values than standalone TS, genetic algorithm (GA), random search (RS), and iterative local search (ILS) across various problem scales. This research contributes to the current body of knowledge by introducing a comprehensive framework that improves VM operational performance and serves as a practical resource for optimizing the logistics and profitability within VM networks.

自动售货机（vm）是自动化零售的一个重要方面，为消费者提供操作的灵活性和便利性。然而，随着虚拟机网络的扩展，管理人员在确定最佳部署位置、产品选择和分配以及重新进货计划方面面临着越来越多的后勤挑战。本研究提出了一种新的双层优化框架，共同优化部署、产品选择和分配以及同步补货周期。为了解决这种大规模组合问题的复杂性，我们开发了一种混合禁忌搜索和进化策略（TS-ES）算法。大量实验表明，同步补货周期比独立补货周期具有更好的性能。对比分析表明，在不同的问题尺度上，混合TS- es算法均比独立TS、遗传算法（GA）、随机搜索（RS）和迭代局部搜索（ILS）获得更高的目标值。本研究通过引入一个全面的框架来提高虚拟机的运行性能，并作为虚拟机网络中优化物流和盈利能力的实用资源，为当前的知识体系做出了贡献。

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引用次数: 0

A scenario-adaptive optimization model for circular intertwined supply network design under uncertainty 不确定条件下循环交织供电网络设计的场景自适应优化模型

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-25 DOI: 10.1016/j.cie.2026.111849

Mohaddeseh Roshan , Jessica Olivares-Aguila , Waguih ElMaraghy

Intertwined supply networks are collaborative, cross-industry supply chains characterized by a high level of interconnectedness among their entities. This study demonstrates that integrating circular economy principles into such networks can cut greenhouse gas emissions by 4.97% and reduce total system costs by 11.03%, while strengthening economic efficiency and social responsibility under uncertainty. To realize these improvements, a novel multi-objective non-linear mixed-integer mathematical model is proposed with an embedded scenario differentiation mechanism that enables evaluation of configurations, from traditional decentralized supply chains to complex intertwined networks with varying levels of circularity, within a unified analytical model. The objective functions are to minimize system costs and greenhouse gas emissions and maximize social responsibility for optimal location decisions under uncertainty. The proposed model is first verified using the AUGMECON-2 method and validated via a case study of an intertwined pharmaceutical-bioplastic supply network, complemented by numerical experiments, sensitivity analyses, and a comparative study using the Grey Wolf Optimizer for large-scale instances.

交织的供应网络是协作的、跨行业的供应链，其特点是其实体之间的高度互联性。研究表明，将循环经济原则融入此类网络可减少4.97%的温室气体排放，降低11.03%的系统总成本，同时增强不确定性下的经济效率和社会责任。为了实现这些改进，提出了一种新的多目标非线性混合整数数学模型，该模型具有嵌入式场景区分机制，可以在统一的分析模型中对配置进行评估，从传统的分散供应链到具有不同循环水平的复杂交织网络。不确定条件下最优选址决策的目标函数是系统成本和温室气体排放最小化，社会责任最大化。首先使用AUGMECON-2方法验证了所提出的模型，并通过一个相互交织的制药-生物塑料供应网络的案例研究进行了验证，并辅以数值实验、敏感性分析和使用灰狼优化器进行大规模实例的比较研究。

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引用次数: 0

Simulation-based optimization of industrial symbiosis under carbon regulations: towards sustainable and resilient production networks 碳监管下基于模拟的工业共生优化：走向可持续和有弹性的生产网络

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-25 DOI: 10.1016/j.cie.2026.111847

Lina Aboueljinane , Maroua Sbiti , Youness Frichi

While Industrial Symbiosis (IS) is a cornerstone of the circular economy, its operational viability remains vulnerable to market volatility and regulatory shifts. This study investigates the resilience and sustainability of a symbiotic system under five carbon regulation mechanisms. A capacitated joint production planning problem is formulated as a Mixed-Integer Linear Program (MILP) and compared against a Simulation-Based Optimization framework using Differential Evolution (DE). To evaluate global robustness, we conducted a massive stress-test across 5000 scenarios generated via Latin Hypercube Sampling (LHS) and analyzed using Explainable AI (Random Forest). The results reveal a critical “Structural Fragility”: the deterministic MILP exhibits a 60% failure rate, categorized either as Mathematical Infeasibility (solver incapacity) or Physical Operational Failure (inventory overflows during simulation), driven by capacity bottlenecks and demand surges. In contrast, the proposed framework guarantees 99.76% % feasibility by dynamically adjusting safety stocks, identifying robust “best-effort” solutions. A multi-objective Pareto analysis further quantifies the trade-offs, revealing a Shadow Price of Resilience and an Environmental Rebound Effect. Among regulatory mechanisms, Cap-and-Trade emerges as the “smartest“ policy, enabling a dynamic arbitrage capability, where the system intelligently switches between production and carbon trading based on market signals. This study contributes a unified, data-driven framework for designing resilient, low-carbon manufacturing systems capable of withstanding real-world uncertainty.

虽然工业共生（IS）是循环经济的基石，但其运营可行性仍然容易受到市场波动和监管变化的影响。本研究探讨了五种碳调控机制下共生系统的恢复力和可持续性。将有能力联合生产计划问题表述为混合整数线性规划（MILP），并与基于仿真的差分进化优化框架进行了比较。为了评估全局稳健性，我们通过拉丁超立方体采样（LHS）对5000个场景进行了大规模的压力测试，并使用可解释人工智能（随机森林）进行了分析。结果揭示了一个关键的“结构脆弱性”：确定性的MILP显示出60%的失败率，被分类为数学上的不可行性（求解器无能）或物理操作失败（模拟期间的库存溢出），由产能瓶颈和需求激增驱动。相比之下，提议的框架通过动态调整安全库存，确定稳健的“尽力而为”解决方案，保证99.76%的可行性。多目标帕累托分析进一步量化了权衡，揭示了弹性的影子价格和环境反弹效应。在监管机制中，总量管制与交易成为“最聪明”的政策，实现了动态套利能力，系统根据市场信号在生产和碳交易之间智能切换。该研究为设计能够承受现实世界不确定性的弹性低碳制造系统提供了统一的数据驱动框架。

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引用次数: 0

Reconfigurable operation-loop network modeling and resilience optimization considering mission load 考虑任务负荷的可重构操作环网络建模与弹性优化

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-23 DOI: 10.1016/j.cie.2026.111836

Yuheng Dang , Hengte Du , Xu Wang , Xing Pan

Multi-agent systems (MAS), as a representative complex system, have become crucial for analyzing cluster and heterogeneous behaviors in various domains such as biology, social science, military weapon and manufacturing. The MAS exhibits adaptability to environmental changes and can dynamically reconfigure its structure to enhance resilience while reducing vulnerability. However, existing research primarily focuses on proposing reconfiguration strategies to enhance resilience but lacks in-depth exploration of reconfigurable design and capability constraints. The study proposes a reconfigurable operation-loop network (RON) model for resilience analysis and reconfigurable design of MAS based on the operation loop. Subsequently, the performance measurement and resilience metric are presented for RON considering mission load. Furthermore, the mathematical model and optimization framework of reconfiguration are established with the consideration of reconfigurable attributes and the resilience objective. Finally, the feasibility, effectiveness, and superiority of the proposed models and metrics are illustrated through extensive experiments on case based on an emergency response system. Numerical results demonstrate that the performance metric considering mission load contributes to a more accurate assessment of RON resilience than conventional network metrics. This work could yield valuable insights for the reconfigurable and resilient design of MAS, while providing guidance and serving as a reference for future research efforts.

多智能体系统（MAS）作为一种具有代表性的复杂系统，在生物学、社会科学、军事武器和制造业等各个领域已成为分析聚类和异构行为的重要工具。MAS具有对环境变化的适应性，可以动态地重新配置其结构以增强弹性，同时降低脆弱性。然而，现有的研究主要集中在提出重构策略以增强弹性，而缺乏对重构设计和能力约束的深入探索。提出了一种基于运行环的可重构运行环网络模型，用于MAS的弹性分析和可重构设计。在此基础上，提出了考虑任务载荷的RON的性能度量和弹性度量。在此基础上，建立了考虑可重构属性和弹性目标的重构数学模型和优化框架。最后，通过基于应急响应系统的大量案例实验，说明了所提出模型和指标的可行性、有效性和优越性。数值结果表明，与传统网络指标相比，考虑任务负载的性能指标能够更准确地评估网络弹性。这项工作可以为MAS的可重构和弹性设计提供有价值的见解，同时为未来的研究工作提供指导和参考。

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引用次数: 0

An efficient service composition optimization method for Cloud manufacturing based on an IPSO-VIKOR hybrid method 基于IPSO-VIKOR混合方法的云制造高效服务组合优化方法

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-23 DOI: 10.1016/j.cie.2026.111831

Tao Yang , Fang Jiang , Jing Fan , Jiafu Su , Wei Chen

Cloud manufacturing (CMfg) has emerged as a transformative paradigm facilitating the service-oriented transition of manufacturing enterprises. A pivotal challenge within CMfg is service composition and optimal selection (SCOS)—the process of identifying the best combination of services from distributed virtual resource pools to meet customized requirements. However, existing SCOS evaluation frameworks often lack systematic indicators for green production, consequently failing to align with increasingly stringent environmental regulations and hindering sustainable development. To bridge this gap, this paper introduces a comprehensive three-dimensional evaluation system that integrates environment, service performance, and service collaboration dimensions, employing a game-theoretic approach to assign comprehensive weights. Subsequently, a service composition and optimal selection model incorporating corporate green manufacturing (SCOS-CGM) is proposed. To address the SCOS-CGM model, we develop a hybrid approach combining an Improved Particle Swarm Optimization Algorithm with the VIKOR method (IPSO-VIKOR). Finally, a case study involving electric drive systems for new energy vehicles validates the practical applicability and effectiveness of the proposed model and method.

云制造已经成为推动制造企业向服务型转型的变革范式。CMfg中的一个关键挑战是服务组合和最优选择（SCOS）——从分布式虚拟资源池中确定最佳服务组合以满足定制需求的过程。然而，现有的SCOS评价框架往往缺乏绿色生产的系统指标，因此不符合日益严格的环境法规，阻碍了可持续发展。为了弥补这一差距，本文引入了一个综合的三维评估系统，该系统集成了环境，服务绩效和服务协作维度，采用博弈论方法分配综合权重。在此基础上，提出了基于企业绿色制造的服务组合与优化选择模型。为了解决SCOS-CGM模型，我们开发了一种结合改进粒子群优化算法和VIKOR方法（IPSO-VIKOR）的混合方法。最后，以新能源汽车电驱动系统为例，验证了所提模型和方法的实用性和有效性。

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引用次数: 0

Data-driven departure time and traffic assignment model for intercity multimodal transport system 数据驱动的城际多式联运系统出发时间与交通分配模型

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-22 DOI: 10.1016/j.cie.2026.111834

Di Huang, Ziyu Liu, Tianle Li, Ziyuan Gu

Developed transportation infrastructure facilitates intercity commuting, which is characterized by closed highway systems, fixed schedules for modes of rail transit, requiring precise synchronization of arrival and departure times. Consequently, integrated decision-making involving mode, route, and departure time across both intracity and intercity segments is essential. However, most departure time user equilibrium (DTUE) studies focus on single cities, overlooking the interaction between intracity and intercity travel decisions. While extensive historical travel data exist, directly using all data to reduce computational efficiency is complicated by daily fluctuations. Thus, identifying historical scenarios matching current conditions is crucial. Given the limited interpretability of prediction models, this paper proposes a Jaccard mean square similarity (JMSS) based historical result filtering method to ensure historical results reflect current scenarios. A super network integrating multimodal intercity and intracity travel is introduced, allowing travelers to move between cities seamlessly. A quasi-dynamic traffic assignment algorithm considering residual queues is developed to solve the DTUE problem, accounting for rail transit’s periodic operation and passenger transfer demands. Results show JMSS maintains low computation time, and increased similarity reduces iterations for convergence and total computation time. Furthermore, rising travel demand compels more travelers to adjust departure times earlier or later to minimize generalized travel costs, with rail transit becoming a preferred option for many due to its stable scheduling and lower congestion impact.

发达的交通基础设施促进了城际通勤，其特点是封闭的高速公路系统，固定的轨道交通模式时间表，需要精确同步的到达和离开时间。因此，综合决策包括模式、路线和出发时间在城市和城际段是必不可少的。然而，大多数出发时间用户平衡（DTUE）研究都集中在单个城市，忽视了城际和城内旅行决策之间的相互作用。虽然存在大量的历史旅行数据，但直接使用所有数据来降低计算效率因日常波动而变得复杂。因此，确定与当前条件相匹配的历史情景至关重要。鉴于预测模型的可解释性有限，本文提出了一种基于Jaccard均方相似度（JMSS）的历史结果过滤方法，以确保历史结果反映当前场景。引入了一个集城际和城市旅行多式联运的超级网络，让旅客在城市之间无缝移动。考虑轨道交通的周期性运行和乘客换乘需求，提出了一种考虑剩余队列的准动态交通分配算法。结果表明，JMSS保持了较低的计算时间，相似度的增加减少了收敛的迭代次数和总计算时间。此外，不断增长的出行需求迫使更多的旅行者提前或推迟出发时间，以最大限度地降低总体出行成本，而轨道交通由于其稳定的调度和较低的拥堵影响，成为许多人的首选。

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引用次数: 0

Optimization of carriage parking based on simulation of passenger dynamics in the dynamic autonomous non-stop rail transit system 动态自主不间断轨道交通系统中基于乘客动力学仿真的车厢停车优化

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-22 DOI: 10.1016/j.cie.2026.111842

Pei-Yang Wu , Ren-Yong Guo , Ying-En Ge

This study investigates the carriage parking problem in the dynamic autonomous non-stop rail transit (DANRT) system, with a particular focus on the movement behaviors of passengers. A cell transmission model (CTM) is formulated to depict the movement behaviors of passengers in the DANRT system and the interactions between passengers. The parameters in the CTM are calibrated by using a set of video recordings and reproducing the arching phenomenon of passengers. To optimize carriage parking schemes, a swarm intelligence-based heuristic algorithm is proposed, where the CTM is embedded into the evaluation process to dynamically assess passenger moving efficiency during each iteration. We conduct a set of numerical experiments to evaluate the effect of algorithm parameters on algorithm performance and the influence of passenger behaviors on passenger waiting times. The results demonstrate that the algorithm can further reduce the theoretical minimum total passenger waiting time obtained without considering passenger movement behaviors and interactions by about 6%. Additionally, overall system efficiency reaches its maximum when the frequency of carriage re-selection behavior of passengers remains at a moderate level. Moreover, it is essential to deliberately designate carriages for passengers to improve the travel efficiency of passengers in the DANRT system.

本文研究了动态自主不间断轨道交通（DANRT）系统中的车厢停车问题，重点关注乘客的移动行为。建立了一个细胞传递模型（CTM）来描述乘客在DANRT系统中的运动行为和乘客之间的相互作用。CTM中的参数是通过一组录像和再现乘客的弓形现象来校准的。为了优化车厢停车方案，提出了一种基于群体智能的启发式算法，该算法将CTM嵌入到评估过程中，在每次迭代中动态评估乘客的移动效率。我们通过一组数值实验来评估算法参数对算法性能的影响以及乘客行为对乘客等待时间的影响。结果表明，在不考虑乘客运动行为和相互作用的情况下，该算法可将理论最小乘客总等待时间进一步减少约6%。此外，当乘客改选行为的频率保持在中等水平时，系统整体效率达到最大。此外，在公交系统中，为了提高乘客的出行效率，有针对性地为乘客指定车厢是非常必要的。

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引用次数: 0

A rolling horizon based bi-objective optimization approach for dynamic truck dispatching with cross-dock door assignment 基于滚动视界的货车动态调度双目标优化方法

IF 6.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2026-01-20 DOI: 10.1016/j.cie.2026.111826

Xinghan Chen , Yuzhilin Hai , Maoxiang Lang

This study investigates a bi-objective joint scheduling problem of vehicle dispatching with cross-dock door assignment (VDCDAP) in the intelligent warehouse system of a less-than-truckload (LTL) logistics hub, aiming to minimize both the total operation delay time (for trucks) and makespan (for dock doors). To accommodate real-time operational dynamics, we introduce a relaxed time window to mitigate discrepancies between expected and actual parallel cross-docking timelines. A rolling horizon-based adaptive large neighborhood search (RH-ALNS) algorithm is developed to solve the model, which considers heterogeneous trucks and dock doors operating under mixed service modes. By deferring real-time demand for centralized scheduling, the entire timeline is discretized into multiple time horizons, allowing the system to respond to dynamic task requirements. As a case study, the proposed approach is applied to a real-world LTL logistics hub in China. The results show that the optimization approach not only yields scheduling schemes that simultaneously dispatch trucks, assign dock doors, and generate operational sequencing timetables, but also significantly improves operational fluency and cross-dock utilization. Moreover, it closely approximates online scheduling with a CPU time of 158 s per 60 min. The developed algorithm is experimentally compared with other solvers and heuristics, proved to be beneficial for obtaining robust solutions across different case scales, service modes, and time horizons.

摘要本文研究了一种集散物流中心智能仓库系统中具有跨码头门分配的车辆调度（VDCDAP）的双目标联合调度问题，以最小化总运行延迟时间（卡车）和最大完工时间（码头门）。为了适应实时操作动态，我们引入了一个宽松的时间窗口，以减轻预期和实际平行交叉对接时间线之间的差异。针对混合服务模式下的异构货车和船坞门，提出了一种基于滚动地平线的自适应大邻域搜索算法。通过延迟集中调度的实时需求，整个时间线被离散到多个时间范围，允许系统响应动态任务需求。作为一个案例研究，提出的方法应用于现实世界的LTL物流中心在中国。结果表明，该优化方法不仅能产生同时调度卡车、分配码头门和生成作业排序时间表的调度方案，而且能显著提高作业流畅性和跨码头利用率。此外，它非常接近在线调度，CPU时间为每60分钟158秒。实验结果表明，该算法能够在不同的案例规模、服务模式和时间范围内获得较好的鲁棒解。

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引用次数: 0