Computers & Industrial Engineering最新文献_第5页

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

Enhancing supply chain viability through dynamic adaptation: a simulation-based approach to scalability and substitution strategies 通过动态适应增强供应链生存能力：基于模拟的可扩展性和替代策略方法

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.2026.111835

Marta Rinaldi , Eric H. Grosse

The COVID-19 pandemic has affected the global economy, increasing the focus on resilience and survivability in supply chains (SCs). This study addresses these topics and advances understanding of how strategic decisions can enhance supply chain viability under adverse conditions. It integrates empirical case studies and simulation modeling to investigate two SC adaptation strategies and their impact on SC performance. A dynamic supplier selection process based on scalability and substitution was implemented, and varied thresholds and time horizons were tested and evaluated. This study makes significant contributions to the literature by integrating the constructs of resilience and efficiency, offering valuable insights for academics and practitioners. The results demonstrate how a combination of scalability and substitution can enhance SC viability while maintaining SC performance. Integrating simulation results with real-world case study data enriches the literature by bridging the gap between theory and practice and providing actionable managerial insights to enhance both strategic planning and operational viability in SCs.

2019冠状病毒病大流行影响了全球经济，使人们更加关注供应链的抵御能力和生存能力。本研究解决了这些问题，并推进了对战略决策如何在不利条件下提高供应链生存能力的理解。本文结合实证案例研究和仿真模型，探讨了两种供应链适应策略及其对供应链绩效的影响。实现了基于可扩展性和可替代性的动态供应商选择过程，并对不同的阈值和时间范围进行了测试和评估。本研究整合了弹性和效率的概念，为学术界和实践者提供了有价值的见解。结果表明，可扩展性和替代的结合如何在保持供应链绩效的同时提高供应链的生存能力。将模拟结果与现实世界的案例研究数据相结合，通过弥合理论与实践之间的差距，并提供可操作的管理见解，以增强SCs的战略规划和运营可行性，丰富了文献。

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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

Optimizing emergency rescue operations: A computerized intelligent system for UAV communication relay planning 优化应急救援行动：无人机通信中继规划的计算机智能系统

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.2026.111844

Xiaosheng Ni , Songyi Wang , Xiongbin Yu , Changjie Hu , Xing Luo , Xiong Li , Jingpu Duan

To address communication disruptions in disaster areas, a critical challenge in crisis and operations management and telecommunications infrastructure recovery, this paper proposes a computerized intelligent system for UAV emergency communication relay operations that integrates intelligent sensing with cooperative planning for rapid network restoration. The system first employs a multi-modal fusion framework, utilizing visual and signal data to accurately assess the health status of base stations (BSs), which provides a reliable knowledge base for subsequent operational planning. Based on this real-time assessment, a dual-layer hierarchical path planning algorithm is then introduced. This algorithm generates optimal patrol paths for irregularly shaped coverage areas containing voids by leveraging standard optimization techniques based on segment decomposition and the traveling salesman problem. Simulation results demonstrate the design and accuracy of the proposed identification framework. Compared to the traditional random patrol algorithm, the path planning algorithm improves operational efficiency by nearly four times under a 95% coverage requirement and exhibits excellent scalability. Furthermore, a dual-UAV cooperative operation mode can reduce mission completion time by an additional 41%. Large-scale scenario simulations validate the computational stability of the hierarchical decomposition mechanism and reveal the nonlinear relationship between resource investment and efficiency. This research provides a closed-loop, efficient intelligent system framework for emergency communication recovery, linking intelligent situation awareness to dynamic operational planning.

针对灾区通信中断这一危机运营管理和电信基础设施恢复面临的关键挑战，本文提出了一种集成智能感知和协同规划的无人机应急通信中继操作计算机智能系统，用于快速恢复网络。该系统首先采用多模态融合框架，利用视觉和信号数据准确评估基站（BSs）的健康状态，为后续运营规划提供可靠的知识库。在此基础上，提出了一种双层分层路径规划算法。该算法利用基于分段分解和旅行商问题的标准优化技术，在包含空洞的不规则覆盖区域生成最优巡逻路径。仿真结果验证了所提识别框架的设计和准确性。与传统的随机巡逻算法相比，在95%的覆盖率要求下，路径规划算法的运行效率提高了近4倍，并具有良好的可扩展性。此外，双无人机协同操作模式可以将任务完成时间额外减少41%。大规模场景仿真验证了分层分解机制的计算稳定性，揭示了资源投入与效率之间的非线性关系。该研究为应急通信恢复提供了一个闭环、高效的智能系统框架，将智能态势感知与动态作战计划联系起来。

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引用次数: 0

A proposed local search strategy and neighborhoods for solving a new variant of e-commerce districting problem 提出了一种解决新型电子商务分区问题的局部搜索策略和邻域

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.2026.111843

Van Son Nguyen, Quang Dung Pham, Quoc Trung Bui, Thuy Chau Tran

A districting problem with multiple-activity balancing is a key operational challenge in e-commerce logistics, where a large geographical area is divided into smaller zones allocated to drivers. The objective is to group such zones into a number of balanced operating districts and then assign them to drivers based on specific planning criteria. Optimizing these districts enables e-commerce companies to reduce operational costs while ensuring high delivery service quality. This paper introduces a novel variant of the p-Median districting problem, incorporating real-world factors inspired by one of the largest e-commerce companies in Southeast Asia. Our work considers significant workload differences between small zones and the driver’s familiarity. We formulate the considered problem as a mixed-integer linear programming model and propose an efficient local search framework to solve it. The novelty of our approach lies in designing new neighborhood structures to address workload imbalances in non-adjacent districts. To evaluate our proposed algorithm, numerical experiments are performed on both randomly generated and real-world instances. The proposed algorithm outperforms the location–allocation method developed by our partner company and some state-of-the-art methods in the literature, delivering high-quality solutions within a reasonable time. Thus, it is well-suited for real-world applications.

多活动平衡的分区问题是电子商务物流中一个关键的运营挑战，在电子商务物流中，一个大的地理区域被划分成更小的区域，分配给司机。目标是将这些区域划分为若干平衡的运营区域，然后根据具体的规划标准将其分配给司机。优化这些地区可以使电子商务公司在确保高交付服务质量的同时降低运营成本。本文介绍了p-中位数划分问题的一个新变体，结合了东南亚最大的电子商务公司之一所启发的现实世界因素。我们的研究考虑了小区域和驾驶员熟悉程度之间的显著工作量差异。我们将所考虑的问题表述为一个混合整数线性规划模型，并提出了一个有效的局部搜索框架来求解它。我们的方法的新颖之处在于设计新的社区结构，以解决非邻近地区的工作量不平衡问题。为了评估我们提出的算法，在随机生成和现实世界的实例上进行了数值实验。该算法优于合作伙伴公司开发的位置分配方法和文献中一些最先进的方法，在合理的时间内提供高质量的解决方案。因此，它非常适合实际应用程序。

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引用次数: 0

On planning cost-efficient and flexible aircraft maintenance operations: Technician shift scheduling and task assignment over multiple bases 在计划成本效益和灵活的飞机维修操作：技术员轮班安排和任务分配在多个基地

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

Computers & Industrial Engineering

Pub Date : 2026-01-19 DOI: 10.1016/j.cie.2026.111801

José Ignacio Sanhueza , Felipe Delgado , Mathias A. Klapp

Airlines often outsource aircraft maintenance to third-party providers. As maintenance demand fluctuates, providers must dynamically plan in-house technician schedules, assign tasks to individual technicians, and determine when to rely on external resources, such as on-call shifts or outsourced work.

We study how a maintenance provider should decide where (i.e., at which base), when (i.e., within each aircraft’s ground-time window), and by whom (i.e., which in-house technician) to perform each job to make an efficient use of resources and minimize external costs. We model this problem as an integer program and solve it via a Price-and-Branch heuristic with customized pricing models that identify profitable technician work patterns. We present several pricing model variants to explore different forms of technician labor flexibility, including multi-skilling, temporal flexibility (i.e., assigning different shift start times to technicians across workdays), and spatial flexibility (i.e., relocating technicians among maintenance bases).

Using data from a maintenance provider, we quantify the potential cost savings associated with each source of labor flexibility. Compared to a base case, multi-skilled technicians offer the most significant cost reductions (48.5%), while the independent use of spatial and temporal flexibilities yields average reductions of 13% and 15%, respectively. Moreover, we observe that most benefits can be achieved with only a fraction of multi-skilled technicians. Overall, our approach obtains a potential cost reduction between 78% and 93%, when compared to a heuristic method that emulates a common practice of maintenance planners.

航空公司经常将飞机维修外包给第三方供应商。随着维护需求的波动，供应商必须动态规划内部技术人员的时间表，将任务分配给个别技术人员，并确定何时依赖外部资源，如随叫随到或外包工作。我们研究维修供应商应该如何决定在哪里（即，在哪个基地），何时（即，在每架飞机的地面时间窗口内），以及由谁（即，哪个内部技术人员）执行每项工作，以有效利用资源并最大限度地减少外部成本。我们将这个问题建模为一个整数程序，并通过价格和分支启发式方法解决它，该启发式方法具有定制的定价模型，可以识别有利可图的技术人员工作模式。我们提出了几种定价模型变体，以探索不同形式的技术人员劳动灵活性，包括多技能、时间灵活性（即，在不同工作日为技术人员分配不同的轮班开始时间）和空间灵活性（即，在维修基地之间重新安置技术人员）。使用来自维护提供商的数据，我们量化了与每个劳动力灵活性来源相关的潜在成本节约。与基本情况相比，多技能技术人员的成本降低幅度最大（48.5%），而独立使用空间和时间灵活性的成本平均分别降低13%和15%。此外，我们观察到，只有一小部分多技能技术人员才能实现大多数好处。总的来说，与模拟维护计划的常见实践的启发式方法相比，我们的方法获得了78%到93%的潜在成本降低。

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引用次数: 0

Minimax truncated repetitive Weibull reliability demonstration test planning 极大极小截断重复威布尔可靠性论证试验计划

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

Computers & Industrial Engineering

Pub Date : 2026-01-16 DOI: 10.1016/j.cie.2026.111833

Arturo J. Fernández

Optimal truncated repetitive test plans are developed for reliability demonstration under the assumption that lifetimes follow a Weibull distribution and failure probabilities have a beta distribution. The resulting beta-binomial sampling schemes are derived by minimizing the maximum expected inspection effort while satisfying consumer and producer risk constraints. Integer nonlinear programming is used to determine minimax solutions based on failure count data from the Weibull model. In most scenarios, overdispersion has limited impact on the resulting minimax plans. The proposed methodology is illustrated using reliability testing data from silicon electronic device manufacturing. Compared to traditional single and repetitive sampling schemes, the optimized truncated repetitive test plans generally require fewer samples at worst-case levels. The approach is particularly suitable for applications involving high-cost devices and is beneficial for enhancing confidence between manufacturers and customers.

在寿命服从威布尔分布和失效概率服从beta分布的假设下，提出了用于可靠性论证的最优截断重复试验方案。在满足消费者和生产者风险约束的同时，最小化最大期望检查工作量，从而得到β -二项抽样方案。基于威布尔模型的故障计数数据，采用整数非线性规划方法确定最大最小解。在大多数情况下，过度分散对最终的极大极小计划影响有限。采用硅电子器件制造的可靠性测试数据说明了所提出的方法。与传统的单次重复采样方案相比，优化后的截断重复测试方案通常需要更少的最坏情况下的样本。该方法特别适用于涉及高成本设备的应用，有利于增强制造商和客户之间的信任。

引用次数: 0