Computers & Industrial Engineering最新文献_第6页

Multi-objective human-robot collaborative disassembly line balancing considering components remanufacture demand and hazard characteristics 考虑部件再制造需求和危险特性的多目标人机协作拆卸线平衡

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-09 DOI: 10.1016/j.cie.2024.110621

Disassembly enterprises face significant challenges in managing increasingly intensive workloads with a workforce alone. To address this, current study focuses on balancing a human-robot collaborative disassembly line. For the task operator allocation problem, a mapping constraint mechanism between the disassembly tasks and the task operators is established based on the remanufacture demand and hazard characteristics of components. A mixed-integer programming model is formulated, encompassing four optimization objectives: the number of workstations, the task operator idle balancing index, the demand index, and the hazard index. A novel modified teaching and learning optimization approach is proposed for the addressed human-robot collaborative disassembly line balancing problem. A two-layer encoding strategy is designed based on the solving characteristics of the problem and an embedded perturbation strategy based on randomly transforming the task operator is introduced to enhance the optimization performance of the proposed method. The validity of the mixed-integer programming model and the efficacy of the proposed algorithm are demonstrated through two small-scale human-robot collaborative disassembly case studies. The proposed algorithm is then applied to two real-life cases of human-robot collaborative disassembly lines with different scales. The results of the proposed optimization method are compared with other advanced algorithms, demonstrating its superior performance in both single-objective and multi-objective optimization based on multiple evaluation indicators.

拆卸企业在仅靠劳动力管理日益密集的工作量方面面临巨大挑战。为解决这一问题，当前的研究侧重于平衡人机协作拆卸生产线。针对任务操作员分配问题，基于再制造需求和部件的危险特性，建立了拆卸任务和任务操作员之间的映射约束机制。混合整数编程模型包括四个优化目标：工作站数量、任务操作员空闲平衡指数、需求指数和危险指数。针对所解决的人机协作拆卸线平衡问题，提出了一种新颖的修正教学优化方法。根据问题的求解特点设计了双层编码策略，并引入了基于随机变换任务算子的嵌入式扰动策略，以提高所提方法的优化性能。通过两个小型人机协作拆卸案例研究，证明了混合整数编程模型的有效性和所提算法的有效性。然后将所提出的算法应用于两个不同规模的人机协作拆卸生产线的实际案例。将所提优化方法的结果与其他先进算法进行了比较，证明了其在基于多个评价指标的单目标和多目标优化中的优越性能。

{"title":"Multi-objective human-robot collaborative disassembly line balancing considering components remanufacture demand and hazard characteristics","authors":"","doi":"10.1016/j.cie.2024.110621","DOIUrl":"10.1016/j.cie.2024.110621","url":null,"abstract":"<div><div>Disassembly enterprises face significant challenges in managing increasingly intensive workloads with a workforce alone. To address this, current study focuses on balancing a human-robot collaborative disassembly line. For the task operator allocation problem, a mapping constraint mechanism between the disassembly tasks and the task operators is established based on the remanufacture demand and hazard characteristics of components. A mixed-integer programming model is formulated, encompassing four optimization objectives: the number of workstations, the task operator idle balancing index, the demand index, and the hazard index. A novel modified teaching and learning optimization approach is proposed for the addressed human-robot collaborative disassembly line balancing problem. A two-layer encoding strategy is designed based on the solving characteristics of the problem and an embedded perturbation strategy based on randomly transforming the task operator is introduced to enhance the optimization performance of the proposed method. The validity of the mixed-integer programming model and the efficacy of the proposed algorithm are demonstrated through two small-scale human-robot collaborative disassembly case studies. The proposed algorithm is then applied to two real-life cases of human-robot collaborative disassembly lines with different scales. The results of the proposed optimization method are compared with other advanced algorithms, demonstrating its superior performance in both single-objective and multi-objective optimization based on multiple evaluation indicators.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recyclability level and quantity decisions of electronic manufacturers under four recycling systems of extended producer responsibility 四种生产者延伸责任回收制度下电子制造商的可回收水平和数量决策

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-09 DOI: 10.1016/j.cie.2024.110617

Some electronic manufacturers and groups have left or are planning to leave the default recycling system that regulates their responsibilities for end-of-life (EoL) products. A legislative menu in the extended producer responsibility (EPR) framework allows manufacturers to choose the rate or cost model freely. In this paper, we model four potential recycling systems to study how two firms with brand differentiation should choose legislative models. We analyze the effect of take-back rate and brand differentiation on the firms’ equilibrium decisions, identify the condition in which firms leave the default plan, and further compare economic and environmental outcomes among all recycling systems. We find that only the cost system creates free-riding avenues because the current cost allocation mechanism by market shares does not concern the environmental contributions of members. We also find that the hybrid system (which includes rate-cost and cost-rate systems) provides higher design incentives than the basic case (which includes rate and cost systems), contrasting to the conventional wisdom in which the rate system has superior design incentives. Finally, our results demonstrate that the rate-cost system performs better economic and environmental benefits due to the perfect match between differentiated manufacturers and legislative models.

一些电子产品制造商和团体已经退出或计划退出规范其对报废产品（EoL）责任的默认回收系统。生产者延伸责任（EPR）框架中的立法菜单允许制造商自由选择回收率或成本模式。在本文中，我们模拟了四种潜在的回收体系，研究了具有品牌差异的两家公司应如何选择立法模式。我们分析了回收率和品牌差异对企业均衡决策的影响，确定了企业离开默认计划的条件，并进一步比较了所有回收体系的经济和环境结果。我们发现，只有成本制度会产生搭便车的机会，因为目前按市场份额分配成本的机制并不考虑成员对环境的贡献。我们还发现，混合系统（包括费率-成本系统和成本-费率系统）比基本系统（包括费率和成本系统）提供了更高的设计激励，这与传统观点不同，传统观点认为费率系统具有更高的设计激励。最后，我们的研究结果表明，由于差异化制造商和立法模式之间的完美匹配，费率-成本体系具有更好的经济和环境效益。

{"title":"Recyclability level and quantity decisions of electronic manufacturers under four recycling systems of extended producer responsibility","authors":"","doi":"10.1016/j.cie.2024.110617","DOIUrl":"10.1016/j.cie.2024.110617","url":null,"abstract":"<div><div>Some electronic manufacturers and groups have left or are planning to leave the default recycling system that regulates their responsibilities for end-of-life (EoL) products. A legislative menu in the extended producer responsibility (EPR) framework allows manufacturers to choose the rate or cost model freely. In this paper, we model four potential recycling systems to study how two firms with brand differentiation should choose legislative models. We analyze the effect of take-back rate and brand differentiation on the firms’ equilibrium decisions, identify the condition in which firms leave the default plan, and further compare economic and environmental outcomes among all recycling systems. We find that only the cost system creates free-riding avenues because the current cost allocation mechanism by market shares does not concern the environmental contributions of members. We also find that the hybrid system (which includes rate-cost and cost-rate systems) provides higher design incentives than the basic case (which includes rate and cost systems), contrasting to the conventional wisdom in which the rate system has superior design incentives. Finally, our results demonstrate that the rate-cost system performs better economic and environmental benefits due to the perfect match between differentiated manufacturers and legislative models.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A bi-population cooperative scatter search algorithm for distributed hybrid flow shop scheduling with machine breakdown 带机器故障的分布式混合流程车间调度的双群合作散点搜索算法

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-09 DOI: 10.1016/j.cie.2024.110624

The occurrence of machine breakdowns is a frequent and dynamic phenomenon in the production process. The implementation of effective preventive measures can mitigate such events and result in reduced production costs. This paper investigates the distributed hybrid flow shop scheduling problem with machine breakdown (DHFSSPB) considering short maintenance time. The bi-population cooperative scatter search (BCSS) algorithm is proposed to address the DHFSSPB, wherein the search for the optimal scheduling sequence is transformed into genetic evolution aiming to obtain a gene chain with both minimum lower bound and minimum cost attributes. Firstly, the DHFSSPB problem is modeled through a combination of predictive maintenance strategy and right-shift rescheduling rule. Subsequently, a diversification approach is developed to facilitate attribute inheritance, enhance the efficiency of job allocation, and establish a reference set. The reference set is partitioned into two subpopulations based on lower bound attributes and cost attributes, respectively. The corresponding hybrid search strategies are designed to enhance the efficiency of job sorting and machine selection for subpopulations with distinct attributes. The cooperative evolution between subpopulations occurs through the competitive interaction and fusion of individuals. An enhanced reinforcement learning approach is proposed to expedite the acceleration of individual attribute evolution by leveraging evolutionary knowledge acquired from populations, thereby effectively guiding the evolutionary trajectories of individuals. Additionally, a method for evaluating the population during the learning process is developed based on problem characteristics to enhance learning efficiency. Experimental results demonstrate that BCSS outperforms the comparative algorithm in solving the DHFSSPB.

机器故障是生产过程中经常发生的动态现象。实施有效的预防措施可以减少此类事件的发生，从而降低生产成本。本文研究了考虑短维护时间的机器故障分布式混合流水车间调度问题（DHFSSPB）。针对 DHFSSPB 问题，本文提出了双群体合作分散搜索（BCSS）算法，将最优调度序列的搜索转化为遗传进化，旨在获得同时具有最小下限和最小成本属性的基因链。首先，DHFSSPB 问题通过预测性维护策略和右班重排规则的组合来建模。随后，开发了一种多样化方法，以促进属性继承、提高工作分配效率并建立参考集。参考集根据下限属性和成本属性分别划分为两个子群。设计了相应的混合搜索策略，以提高具有不同属性的子群的作业排序和机器选择效率。子群之间的合作进化是通过个体之间的竞争互动和融合实现的。我们提出了一种增强型强化学习方法，通过利用从群体中获取的进化知识来加速个体属性的进化，从而有效地指导个体的进化轨迹。此外，还根据问题特征开发了一种在学习过程中评估种群的方法，以提高学习效率。实验结果表明，在求解 DHFSSPB 时，BCSS 优于比较算法。

{"title":"A bi-population cooperative scatter search algorithm for distributed hybrid flow shop scheduling with machine breakdown","authors":"","doi":"10.1016/j.cie.2024.110624","DOIUrl":"10.1016/j.cie.2024.110624","url":null,"abstract":"<div><div>The occurrence of machine breakdowns is a frequent and dynamic phenomenon in the production process. The implementation of effective preventive measures can mitigate such events and result in reduced production costs. This paper investigates the distributed hybrid flow shop scheduling problem with machine breakdown (DHFSSPB) considering short maintenance time. The bi-population cooperative scatter search (BCSS) algorithm is proposed to address the DHFSSPB, wherein the search for the optimal scheduling sequence is transformed into genetic evolution aiming to obtain a gene chain with both minimum lower bound and minimum cost attributes. Firstly, the DHFSSPB problem is modeled through a combination of predictive maintenance strategy and right-shift rescheduling rule. Subsequently, a diversification approach is developed to facilitate attribute inheritance, enhance the efficiency of job allocation, and establish a reference set. The reference set is partitioned into two subpopulations based on lower bound attributes and cost attributes, respectively. The corresponding hybrid search strategies are designed to enhance the efficiency of job sorting and machine selection for subpopulations with distinct attributes. The cooperative evolution between subpopulations occurs through the competitive interaction and fusion of individuals. An enhanced reinforcement learning approach is proposed to expedite the acceleration of individual attribute evolution by leveraging evolutionary knowledge acquired from populations, thereby effectively guiding the evolutionary trajectories of individuals. Additionally, a method for evaluating the population during the learning process is developed based on problem characteristics to enhance learning efficiency. Experimental results demonstrate that BCSS outperforms the comparative algorithm in solving the DHFSSPB.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The convergence of IoT and sustainability in global supply chains: Patterns, trends, and future directions 全球供应链中物联网与可持续发展的融合：模式、趋势和未来方向

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-09 DOI: 10.1016/j.cie.2024.110631

This study investigates the pivotal role of Internet of Things (IoT) applications in advancing sustainable supply chains through a comprehensive analysis of research trends, international collaborations, and thematic evolution. Utilizing data from the Web of Science database, the research employs an innovative methodological framework combining keyword network analysis, country collaboration networks, and thematic mapping. The study reveals seven distinct keyword communities, highlighting the dominance of enabling technologies and the emergence of sector-specific applications. Analysis of international collaborations identifies five country clusters, each with unique research foci and collaborative patterns. The thematic map and evolution analysis uncover critical research gaps, including underexplored areas such as security in IoT-enabled supply chains and the integration of smart city concepts. The study projects future research directions, emphasizing the convergence of artificial intelligence and IoT, and the need for more holistic approaches to sustainability in supply chain management. The findings underscore the potential of IoT to foster sustainable business models that balance economic, social, and environmental benefits. This research contributes to the growing body of knowledge on IoT applications in sustainable supply chains by providing a multifaceted analysis of the field’s structure, evolution, and future trajectory. The insights offered are valuable for researchers, policymakers, and practitioners seeking to leverage IoT for creating more efficient, resilient, and sustainable supply chains in an increasingly globalized and environmentally conscious market.

本研究通过对研究趋势、国际合作和主题演变的综合分析，探讨了物联网（IoT）应用在推进可持续供应链中的关键作用。本研究利用科学网数据库的数据，采用创新的方法框架，将关键词网络分析、国家合作网络和主题绘图结合起来。研究揭示了七个不同的关键词群，突出了使能技术的主导地位和特定行业应用的出现。国际合作分析确定了五个国家集群，每个集群都有独特的研究重点和合作模式。专题图和演变分析揭示了关键的研究差距，包括物联网供应链的安全性和智慧城市概念的整合等尚未充分开发的领域。研究预测了未来的研究方向，强调了人工智能与物联网的融合，以及在供应链管理中采用更全面的可持续发展方法的必要性。研究结果强调了物联网在促进可持续商业模式方面的潜力，这种商业模式可以兼顾经济、社会和环境效益。这项研究对物联网领域的结构、演变和未来轨迹进行了多方面的分析，为可持续供应链中物联网应用方面不断增长的知识库做出了贡献。所提供的见解对研究人员、决策者和从业人员都很有价值，他们都希望在日益全球化和注重环保的市场中利用物联网创建更高效、更有弹性和更可持续的供应链。

{"title":"The convergence of IoT and sustainability in global supply chains: Patterns, trends, and future directions","authors":"","doi":"10.1016/j.cie.2024.110631","DOIUrl":"10.1016/j.cie.2024.110631","url":null,"abstract":"<div><div>This study investigates the pivotal role of Internet of Things (IoT) applications in advancing sustainable supply chains through a comprehensive analysis of research trends, international collaborations, and thematic evolution. Utilizing data from the Web of Science database, the research employs an innovative methodological framework combining keyword network analysis, country collaboration networks, and thematic mapping. The study reveals seven distinct keyword communities, highlighting the dominance of enabling technologies and the emergence of sector-specific applications. Analysis of international collaborations identifies five country clusters, each with unique research foci and collaborative patterns. The thematic map and evolution analysis uncover critical research gaps, including underexplored areas such as security in IoT-enabled supply chains and the integration of smart city concepts. The study projects future research directions, emphasizing the convergence of artificial intelligence and IoT, and the need for more holistic approaches to sustainability in supply chain management. The findings underscore the potential of IoT to foster sustainable business models that balance economic, social, and environmental benefits. This research contributes to the growing body of knowledge on IoT applications in sustainable supply chains by providing a multifaceted analysis of the field’s structure, evolution, and future trajectory. The insights offered are valuable for researchers, policymakers, and practitioners seeking to leverage IoT for creating more efficient, resilient, and sustainable supply chains in an increasingly globalized and environmentally conscious market.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven vehicle rental and routing optimization: An application in online retailing 数据驱动的车辆租赁和路线优化：在线零售业的应用

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-09 DOI: 10.1016/j.cie.2024.110588

Due to limited self-owned vehicles, online retailers often struggle to meet high demands for deliveries, especially during large promotions. This study employs machine learning to tackle this challenge by shipping products and renting vehicles in advance. We explore a large amount of historical demand data, enabling accurate forecasting of demand information. It is then combined with an improved meta-heuristic algorithm named the Improved Discrete Whale Optimization Algorithm (IDWOA) to help online retailers make optimal decisions. The algorithm involves a discretization method and an effective perturbation strategy, along with information sharing, Cauchy mutation, and an elimination strategy. Experimental results demonstrate that our method can reduce costs by 14.78% compared to temporary vehicle rentals, and it significantly outperforms other comparative algorithms. Therefore, our study effectively integrates machine learning algorithms with an improved meta-heuristic approach, allowing for increased utilization of data-driven advantages to enhance the precision and efficiency of vehicle rental and routing optimization.

由于自备车辆有限，在线零售商往往难以满足大量的送货需求，尤其是在大型促销活动期间。本研究利用机器学习来应对这一挑战，提前运送产品并租用车辆。我们探索了大量历史需求数据，从而能够准确预测需求信息。然后将其与一种名为 "改进离散鲸鱼优化算法"（IDWOA）的改进元启发式算法相结合，帮助在线零售商做出最优决策。该算法包括离散化方法和有效的扰动策略，以及信息共享、考奇突变和消除策略。实验结果表明，与临时车辆租赁相比，我们的方法可以降低 14.78% 的成本，而且明显优于其他比较算法。因此，我们的研究有效地将机器学习算法与改进的元启发式方法结合起来，从而更多地利用数据驱动的优势，提高车辆租赁和路由优化的精度和效率。

引用次数: 0

Traveling salesman problem with time windows and a drone-utilizing intermediate points (TSPTWD-IP) 带时间窗口和无人机利用中间点的旅行推销员问题（TSPTWD-IP）

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-09 DOI: 10.1016/j.cie.2024.110641

The fast growing of e-commerce has raised challenges to the last-mile logistics. Our study focuses on an emerging mode of transportation, i.e., a collaboration of a truck and an autonomous drone to deliver parcels. We develop a novel model of traveling salesman problem with time windows that jointly utilizes a truck and a drone in a coordinated manner. This model allows operating a drone not only on customers’ sites but also on other discrete intermediate points on arcs, and incorporates characteristics not considered previously, such as drone inoperable areas. We formulate this problem as a mixed integer linear program. We also develop a metaheuristic method that can solve the problems with up to 100 customers. Numerical experiments showed that our metaheuristic can find good solutions for many instances. Our model can cut the total delivery time by as much as 26% when compared to the traditional delivery model with only a single truck, and by 4% when compared to the existing model of a truck-and-drone operations that allows a drone to be launched or received at customers’ sites only.

电子商务的快速发展给 "最后一英里 "物流带来了挑战。我们的研究侧重于一种新兴的运输模式，即卡车和自动无人机合作运送包裹。我们开发了一个带有时间窗口的旅行推销员问题新模型，该模型以协调的方式联合使用卡车和无人机。该模型允许无人机不仅在客户所在地而且在弧线上的其他离散中间点上运行，并纳入了以前未考虑过的特性，如无人机不可操作区域。我们将这一问题表述为一个混合整数线性程序。我们还开发了一种元启发式方法，可以解决多达 100 个客户的问题。数值实验表明，我们的元启发式方法可以为许多实例找到良好的解决方案。与只有一辆卡车的传统送货模式相比，我们的模式可以将总送货时间缩短 26%；与现有的卡车加无人机运营模式（只允许在客户所在地发射或接收无人机）相比，我们的模式可以将总送货时间缩短 4%。

引用次数: 0

Neural relational and dynamics inference for complex systems 复杂系统的神经关系和动态推理

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-05 DOI: 10.1016/j.cie.2024.110628

Many complex processes in the real world can be viewed as complex systems and their evolution is governed by underlying nonlinear dynamics. However, one can only access the trajectories of the system without knowing the underlying system structure and dynamics in most cases. To address this challenge, this paper proposes a model called Neural Relational and Dynamics Inference (NRDI) that combines graph neural networks (GNNs) and ordinary differential equation systems (ODEs) to handle both continuous-time dynamics prediction and network topology inference for complex systems. Our model contains two modules: (1) the network inference module, which infers system structure from input system trajectories using GNNs, and (2) the dynamics learning module, which employs GNNs to fit the differential equation system for predicting future trajectories. We tested NRDI’s performance on system trajectory prediction and graph reconstruction separately. Experimental results show that the proposed NRDI outperforms many baseline models on continuous-time complex network dynamics prediction, and can explicitly infer network structures with high accuracy.

现实世界中的许多复杂过程都可以被视为复杂系统，其演变受潜在的非线性动力学支配。然而，在大多数情况下，人们只能获得系统的轨迹，而无法了解系统的基本结构和动力学。为了应对这一挑战，本文提出了一个名为 "神经关系和动力学推断（NRDI）"的模型，该模型结合了图神经网络（GNN）和常微分方程系统（ODE），可处理复杂系统的连续时间动力学预测和网络拓扑推断。我们的模型包含两个模块：(1) 网络推断模块，利用图神经网络从输入系统轨迹推断系统结构；(2) 动力学学习模块，利用图神经网络拟合微分方程系统以预测未来轨迹。我们分别测试了 NRDI 在系统轨迹预测和图重构方面的性能。实验结果表明，在连续时间复杂网络动力学预测方面，所提出的 NRDI 优于许多基线模型，并能高精度地明确推断出网络结构。

引用次数: 0

An integrated distributionally robust model for two-echelon patient appointment scheduling 双梯队病人预约安排的分布稳健综合模型

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-05 DOI: 10.1016/j.cie.2024.110593

We develop a distributionally robust optimization (DRO) model for the outpatient appointment scheduling problem of a set of patients served in two serial stages, consultation and examination. The arrival sequence of patients is known, and the problem of scheduling is to assign appointment time for each patient to minimize total cost with random service time for two serial stages. A max–min problem is formulated for the two-stage appointment scheduling as a whole, in which the waiting time exhibits a high degree of coupling due to the continuous two-stage process. To address this, we devise a two-stage network maximum flow model that provides an equivalent linear expression for the waiting time. For the inner maximum problem, we employ a conic programming approach for equivalent representation, incorporate the scheduling decision of the outer minimum problem, and convert the model to its equivalent copositive programming by taking the conic duality. We conduct numerical experiments and sensitivity analysis using real and simulated data, and the results verify the effectiveness of our proposed DRO model.

我们针对一组病人分咨询和检查两个连续阶段服务的门诊预约调度问题，建立了分布稳健优化（DRO）模型。病人的到达顺序是已知的，调度问题是为每个病人分配预约时间，以最小化两个连续阶段随机服务时间的总成本。针对两阶段预约调度整体提出了一个最大最小问题，其中由于连续的两阶段过程，等待时间表现出高度的耦合性。为此，我们设计了一个两阶段网络最大流量模型，为等待时间提供了一个等效线性表达式。对于内部最大值问题，我们采用圆锥曲线编程方法进行等效表示，纳入外部最小值问题的调度决策，并通过圆锥二重性将模型转换为等效的共正编程。我们利用真实数据和模拟数据进行了数值实验和敏感性分析，结果验证了我们提出的 DRO 模型的有效性。

引用次数: 0

Enhancing group decision-making: Maximum consensus aggregation for fuzzy cross-efficiency under hesitant fuzzy linguistic information 加强群体决策：犹豫模糊语言信息下模糊交叉效率的最大共识聚合

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-04 DOI: 10.1016/j.cie.2024.110622

Group decision-making (GDM) is essential as it recognizes the inherent complexity of many decision scenarios, which frequently require the collective wisdom and knowledge of multiple decision-makers (DMs) to be effectively resolved. The proposed method aims to develop fuzzy data envelopment analysis (DEA) cross-efficiency models tailored to address GDM challenges, wherein attribute values are provided by DMs using hesitant fuzzy linguistic term sets (HFLTSs). For this purpose, we initially transform HFLTSs into their corresponding fuzzy envelopes, defined as trapezoidal fuzzy numbers (TrFNs). This conversion strategy effectively minimizes the loss in assessments based on HFLTSs while retaining the inherent ambiguity of the original information. Building upon this foundation, we develop fuzzy cross-efficiency models by leveraging the

α

-level sets of fuzzy envelopes. These models are designed to handle fuzzy input and output variables under various

α

-level sets, which are capable of considering all possible attribute values for each alternative. Following this, we implement a maximum consensus model using fuzzy cross-efficiency to assign weights to DMs. These weights facilitate the aggregation of individual fuzzy cross-efficiency intervals obtained from DMs’ assessments into collective ones, which serve to rank alternatives. Finally, we showcase the effectiveness and superiority of our proposal through numerical validation and comparative analysis.

群体决策（GDM）是非常重要的，因为它认识到了许多决策情景的内在复杂性，这些情景往往需要多个决策者（DMs）的集体智慧和知识才能有效解决。所提出的方法旨在开发模糊数据包络分析（DEA）交叉效率模型，以解决 GDM 面临的挑战，其中的属性值由 DM 使用犹豫模糊语言术语集（HFLTS）提供。为此，我们首先将 HFLTS 转换为相应的模糊包络，定义为梯形模糊数 (TrFN)。这种转换策略有效地减少了基于 HFLTS 的评估损失，同时保留了原始信息固有的模糊性。在此基础上，我们利用模糊包络的 α 级集开发了模糊交叉效率模型。这些模型旨在处理各种 α 级集合下的模糊输入和输出变量，能够考虑每个备选方案的所有可能属性值。随后，我们利用模糊交叉效率实施最大共识模型，为 DM 分配权重。这些权重有助于将从 DM 评估中获得的单个模糊交叉效率区间汇总为集体区间，从而对备选方案进行排序。最后，我们通过数值验证和比较分析，展示了我们建议的有效性和优越性。

{"title":"Enhancing group decision-making: Maximum consensus aggregation for fuzzy cross-efficiency under hesitant fuzzy linguistic information","authors":"","doi":"10.1016/j.cie.2024.110622","DOIUrl":"10.1016/j.cie.2024.110622","url":null,"abstract":"<div><div>Group decision-making (GDM) is essential as it recognizes the inherent complexity of many decision scenarios, which frequently require the collective wisdom and knowledge of multiple decision-makers (DMs) to be effectively resolved. The proposed method aims to develop fuzzy data envelopment analysis (DEA) cross-efficiency models tailored to address GDM challenges, wherein attribute values are provided by DMs using hesitant fuzzy linguistic term sets (HFLTSs). For this purpose, we initially transform HFLTSs into their corresponding fuzzy envelopes, defined as trapezoidal fuzzy numbers (TrFNs). This conversion strategy effectively minimizes the loss in assessments based on HFLTSs while retaining the inherent ambiguity of the original information. Building upon this foundation, we develop fuzzy cross-efficiency models by leveraging the <span><math><mi>α</mi></math></span>-level sets of fuzzy envelopes. These models are designed to handle fuzzy input and output variables under various <span><math><mi>α</mi></math></span>-level sets, which are capable of considering all possible attribute values for each alternative. Following this, we implement a maximum consensus model using fuzzy cross-efficiency to assign weights to DMs. These weights facilitate the aggregation of individual fuzzy cross-efficiency intervals obtained from DMs’ assessments into collective ones, which serve to rank alternatives. Finally, we showcase the effectiveness and superiority of our proposal through numerical validation and comparative analysis.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Most important performance evaluation methods of production lines: A comprehensive review on historical perspective and emerging trends 生产线最重要的性能评估方法：历史视角和新趋势的全面回顾

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2024-10-03 DOI: 10.1016/j.cie.2024.110623

Production is one of the most significant building blocks that strengthen the sustainable economy of companies and thus contribute to the countries’ welfare. Performance indicators of the production line affect planning operations and the efficiency of the supply chain to which the factory is connected. The key indicators for production line designers and performance analysts to monitor and improve include production rate, resource utilization rate, and average inventory level. The production rate is the most important indicator closely affecting an industrial plant's productivity and efficiency levels. From this perspective, accurate and fast estimation of this indicator is very critical. Production rate can be calculated by simulation, analytical technique, or artificial intelligence methods according to the production line characteristics. In this comprehensive review, the most important performance evaluation methods are discussed historically and systematically about the buffer allocation problem using the snowball sampling method. With this explicit motivation, 145 papers were reviewed and classified according to production line topology, hypothetical/real-case line, machine reliability, previous method on which the method is based, and originality and/or line characteristics. To present a comprehensive comparison, the methods considered were analyzed according to different criteria. This review provides general/in-depth qualitative and quantitative discussions and highlights insights to practitioners and scholars. In addition, the impact of recent key work on production line analysis in the field is assessed along with emerging trends, evolving manufacturing paradigms are discussed, and the challenges associated with performance analysis are addressed.

生产是加强企业可持续经济的最重要基石之一，因此也是国家福利的重要组成部分。生产线的绩效指标会影响工厂的计划运营和供应链的效率。生产线设计师和绩效分析师需要监控和改进的关键指标包括生产率、资源利用率和平均库存水平。生产率是最重要的指标，与工业工厂的生产力和效率水平密切相关。因此，准确、快速地估算这一指标至关重要。根据生产线的特点，生产率可以通过模拟、分析技术或人工智能方法来计算。在这篇综述中，采用雪球抽样法对缓冲区分配问题的最重要性能评估方法进行了历史性和系统性的讨论。基于这一明确的动机，我们对 145 篇论文进行了综述，并根据生产线拓扑结构、假设/实际生产线、机器可靠性、该方法所依据的先前方法以及独创性和/或生产线特征进行了分类。为了进行全面比较，根据不同的标准对所考虑的方法进行了分析。本综述提供了一般/深入的定性和定量讨论，并突出了对从业人员和学者的启示。此外，还评估了生产线分析领域近期重要工作的影响和新兴趋势，讨论了不断演变的制造模式，并探讨了与性能分析相关的挑战。

{"title":"Most important performance evaluation methods of production lines: A comprehensive review on historical perspective and emerging trends","authors":"","doi":"10.1016/j.cie.2024.110623","DOIUrl":"10.1016/j.cie.2024.110623","url":null,"abstract":"<div><div>Production is one of the most significant building blocks that strengthen the sustainable economy of companies and thus contribute to the countries’ welfare. Performance indicators of the production line affect planning operations and the efficiency of the supply chain to which the factory is connected. The key indicators for production line designers and performance analysts to monitor and improve include production rate, resource utilization rate, and average inventory level. The production rate is the most important indicator closely affecting an industrial plant's productivity and efficiency levels. From this perspective, accurate and fast estimation of this indicator is very critical. Production rate can be calculated by simulation, analytical technique, or artificial intelligence methods according to the production line characteristics. In this comprehensive review, the most important performance evaluation methods are discussed historically and systematically about the buffer allocation problem using the snowball sampling method. With this explicit motivation, 145 papers were reviewed and classified according to production line topology, hypothetical/real-case line, machine reliability, previous method on which the method is based, and originality and/or line characteristics. To present a comprehensive comparison, the methods considered were analyzed according to different criteria. This review provides general/in-depth qualitative and quantitative discussions and highlights insights to practitioners and scholars. In addition, the impact of recent key work on production line analysis in the field is assessed along with emerging trends, evolving manufacturing paradigms are discussed, and the challenges associated with performance analysis are addressed.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0