Computers & Industrial Engineering最新文献

{"title":"Smart production strategies for economic growth and environmental sustainability","authors":"Lalremruati Lalremruati,&nbsp;Aditi Khanna","doi":"10.1016/j.cie.2025.111145","DOIUrl":"10.1016/j.cie.2025.111145","url":null,"abstract":"<div><div>This study examines sustainable strategies in a flexible production inventory system to reduce carbon emissions and enhance economic performance. As the need for sustainability in manufacturing intensifies, integrating green technologies and renewable energy sources into production processes emerges as a critical strategy for reducing environmental impact. One significant challenge is the disposal of defective products, which contribute to environmental degradation. To address this, the study proposes a defect management strategy that categorizes defective items into reworkable and recyclable products, offering an opportunity to reduce waste and generate additional revenue. By reprocessing these items into valuable outputs, this strategy not only mitigates environmental degradation but also supports sustainable business growth. A mathematical model is developed to optimize key factors such as selling price, green technology investment, flexible production rates, and production cycles, aiming to maximize overall profit while minimizing carbon emissions. Through in-depth numerical analysis, the study compares different scenarios to assess the economic and environmental benefits of the proposed strategy. The results show that failing to adopt renewable energy reduces profits by 6.53%, excluding defect management strategies leads to a 10.40% profit decrease, and not implementing green technologies results in an 11.31% profit loss. The combination of both defect management and green technologies yields a 12.64% reduction in profits. These findings underscore the significant potential of incorporating sustainable practices in manufacturing, offering a dual advantage of enhancing profitability while minimizing environmental impact.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"205 ","pages":"Article 111145"},"PeriodicalIF":6.7,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882404","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}

{"title":"Enhancing resource sharing in urban rail transit: a rolling stock sharing strategy for multi-line timetable optimization in cross-line operations","authors":"Huabo Lu ,&nbsp;Yan Xu ,&nbsp;Lishan Sun ,&nbsp;Yue Liu ,&nbsp;Xiaolei Ma ,&nbsp;Jianfeng Liu","doi":"10.1016/j.cie.2025.111143","DOIUrl":"10.1016/j.cie.2025.111143","url":null,"abstract":"<div><div>Cross-line operation allows trains to travel between intersecting metro lines, which can provide direct travel for some transfer passengers, thereby alleviating transfer demands at transfer stations. Cross-line operation in urban rail transit allows trains to travel between intersecting lines, reducing transfer demands by enabling direct trips. However, existing studies focus on single-line optimization, lacking strategies for coordinated resource allocation across lines. This paper proposes a rolling stock sharing strategy to enable the sharing of train resources among different lines in cross-line operations. Taking the complex travel processes of both direct and transfer passengers into account, a mixed-integer nonlinear programming model (MINLP) is formulated to optimize train timetables and train resource allocation in cross-line operations, so as to minimize passengers’ waiting time and operating costs. A hybrid algorithm that combines a genetic algorithm, an adaptive large neighborhood search algorithm, and a train operation conflict elimination strategy is designed for the proposed model to find high-quality solutions. Finally, using Line 8 and the Changping Line of the Beijing Metro as a case study, results analysis and five sets of numerical experiments are conducted to prove the effectiveness of the proposed method. The experimental results demonstrate that the method can enhance train resource sharing among depots, improve transport efficiency, and reduce operating costs.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"205 ","pages":"Article 111143"},"PeriodicalIF":6.7,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924413","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}

{"title":"An integrated framework for managing vaccine supply chain shortages in the child immunization program of India","authors":"Dheeraj Chandra ,&nbsp;Shweta ,&nbsp;Amit Kumar Yadav ,&nbsp;Vipul Jain","doi":"10.1016/j.cie.2025.111149","DOIUrl":"10.1016/j.cie.2025.111149","url":null,"abstract":"<div><div>Ensuring a consistent supply of vaccines from manufacture to distribution, storage, and administration relies on efficient management of the Vaccine Supply Chain (VSC). However, in recent years, vaccine shortages have emerged as a major issue for vaccine producers and child immunization programs, especially in low- and middle-income countries, which hampers VSC overall performance. This study aims to address the ongoing problem of vaccine shortages in India’s child immunization program by identifying the main causes and investigating possible solutions to address the shortage issue. To do this, we propose an integrated framework that combines the Analytic Hierarchy Process (AHP) and Complex Proportional Assessment with Grey Theory (COPRAS-G) methodologies. This framework yields 12 potential solutions for the 10 issues causing shortages. We show that demand uncertainty is the primary cause of vaccine shortages and that a better monitoring system is necessary to detect and treat shortages in a timely manner. To validate the stability of the results, we run a Monte Carlo simulation using a uniform probability distribution on the interval [0, 1]. The results of this study will provide valuable insights for policymakers on how to effectively manage the vaccine shortage issue and improve the performance of child immunization programs.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"205 ","pages":"Article 111149"},"PeriodicalIF":6.7,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143911404","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}

{"title":"Optimization of a closed-loop supply chain system considering government incentives mechanism under deep learning algorithms","authors":"Jianquan Guo,&nbsp;Lian Chen,&nbsp;Zhen Wang","doi":"10.1016/j.cie.2025.111146","DOIUrl":"10.1016/j.cie.2025.111146","url":null,"abstract":"<div><div>Against the backdrop of multiple uncertainties, our research endeavors to design a comprehensive closed-loop supply chain system that incorporates dual recycling channels and a series of manufacturing-remanufacturing processes. The focal point of this study lies in the establishment of a holistic profit model aimed at a thorough exploration of the effect of the government incentives mechanism (GIM) on this system. Additionally, we employ deep learning algorithms (DLA), a kind of AI technology, for calculation and solution analysis of the model. The results show: (1) Remanufacturers can develop reasonable recycling, remanufacturing, and manufacturing strategies based on different scenarios; (2) The quality level of recycled products, rather than different demands, has a significant impact on the amount of penalty and reward. Thus, when establishing a GIM to encourage recycling and remanufacturing, the government should primarily focus on the uncertainty of the recycled products’ quality. (3) In the absence of a GIM, remanufacturers are reluctant to strive to improve the recovery rate, and are more inclined to choose informal channels to reduce recovery costs; (4) The GIM can stimulate and regulate enterprises’ recycling activities. Hence, the government should formulate a reasonable GIM to regulate the recycling of enterprises and supervise and guide the transformation and upgrading of informal channels. This research provides profound insights for the establishment of a robust closed-loop supply chain under multiple uncertain environments, and also, this research combines AI technology to improve computational accuracy, provide more reasonable support for business decision-making and government supervision, and provide assistance in realizing a circular economy.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"205 ","pages":"Article 111146"},"PeriodicalIF":6.7,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882401","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}

{"title":"Simulation Optimization-Based model for Decision-Making in the stroke clinical pathway","authors":"Pedro A Boareto ,&nbsp;Leonardo N Moretti ,&nbsp;Juliana Safanelli ,&nbsp;Rafaela B Liberato ,&nbsp;Carla HC Moro ,&nbsp;José E Pécora Junior ,&nbsp;Claudia MCB Moro ,&nbsp;Leandro dos S Coelho ,&nbsp;Eduardo FR Loures ,&nbsp;Fernando Deschamps ,&nbsp;Eduardo A Portela Santos","doi":"10.1016/j.cie.2025.111164","DOIUrl":"10.1016/j.cie.2025.111164","url":null,"abstract":"<div><div>Healthcare is highly complex, sensitive and needs constant improvements. Several works have already been developed to support those processes. However, finding the optimum solution takes much work and time. Multi-Objective Genetic Algorithms (MOGA) improve the results by finding the optimal trade-off between multiple conflicting objectives and exploring the problem space more thoroughly. This study presents an enhanced framework that integrates Process Mining (PM), Discrete Event Simulation (DES), and Multi-Objective Genetic Algorithms (MOGAs) into an optimized, end-to-end pipeline. This framework builds upon an existing non-optimized approach to enable decision-makers to explore and implement Key Performance Indicator (KPI)-oriented solutions directly from raw log data. The framework navigates vast and complex solution spaces by embedding MOGAs into the KPI-oriented simulation process, delivering optimized scenarios with improved performance, boosting decision-making efficiency. The clinical stroke pathway, covering symptoms’ onset to hospital discharge, was utilized as a case. This research demonstrates how optimization techniques with classical techniques into one unified framework can accelerate healthcare improvements, offering scalable applications to other domains beyond stroke care. The results demonstrate that using MOGA leads to improved solutions compared to the non-optimized framework, and this approach can be evaluated in short periods due to its performance. The findings underscore the solutions’ sensitivity to changes in simulation parameters, emphasizing the importance of considering multiple objectives when dealing with complex decision-making problems in the healthcare industry. Future studies are suggested to extend the model, compare the effectiveness of different optimization methods within the framework, and test the framework’s applicability to other domains.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111164"},"PeriodicalIF":6.7,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869588","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}

{"title":"Temporal transaction network anomaly detection for Industrial Internet of Things with federated graph neural networks","authors":"Qingyong Wang ,&nbsp;Beibei Han","doi":"10.1016/j.cie.2025.111122","DOIUrl":"10.1016/j.cie.2025.111122","url":null,"abstract":"<div><div>The Industrial Internet of Things (IIoT) has experienced significant advancements in recent years, resulting in a considerable increase in the volume of data generated by interconnected devices. This surge in data has created new opportunities to enhance the quality of service in machine learning applications within the IIoT through data sharing. Among these applications, anomaly detection in transaction networks utilizing graph neural networks (GNNs) has emerged as a prominent research topic. However, most current anomaly detection methods either focus exclusively on single-faceted transaction information or assume that multiple types of transaction network data are centrally stored or shared. In the field of IIoT scenario, privacy concerns and legal restrictions frequently hinder data centralization, resulting in data islands, which refer to decentralized multisource transaction information. Therefore, we propose a novel <u>fed</u>erated <u>G</u>NNs framework for the <u>t</u>emporal <u>t</u>ransaction network <u>a</u>nomaly <u>d</u>etection, designated as FedGT<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>AD. Specifically, the training process is bifurcated: client-side privacy temporal transaction network feature extraction is conducted locally at its corresponding client, while privacy-protected feature aggregation from all clients occurs on a trusted server. To facilitate more effective anomaly detection, each client initially models edge features and temporal transaction information as node attributes, along with network snapshots for subsequent graph feature computation with GNNs. During the integration process, the server integrates the node-level embedding and computes multisource transaction network features from all clients following a differential privacy mechanism to ensure client-side data security. The experimental results on three decentralized multisource transaction networks demonstrated that FedGT<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>AD outperforms baseline methods by 0.9% to 2.7% in accuracy. Overall, FedGT<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>AD offers a promising approach for mining decentralized multisource transaction networks while preserving privacy in anomaly detection tasks.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"205 ","pages":"Article 111122"},"PeriodicalIF":6.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887071","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}

{"title":"Line balancing for energy efficiency in production: A qualitative and quantitative literature analysis","authors":"Julian Petersen ,&nbsp;Amir Nourmohammadi ,&nbsp;Masood Fathi ,&nbsp;Morteza Ghobakhloo ,&nbsp;Madjid Tavana","doi":"10.1016/j.cie.2025.111144","DOIUrl":"10.1016/j.cie.2025.111144","url":null,"abstract":"<div><div>In the rapidly evolving landscape of hyperconnected digital manufacturing, known as Industry 4.0, achieving energy efficiency has become a critical priority. As manufacturers worldwide strive to meet sustainable development goals, enhancing energy efficiency is essential for reducing operational costs and minimizing environmental impact. In this context, line balancing is a pivotal strategy for optimizing energy consumption within manufacturing processes. This study presents a comprehensive literature review on the Line Balancing Problems (LBPs) focused on enhancing energy efficiency. The review aims to provide a holistic understanding of this domain by examining past, present, and future trends. A systematic literature review is conducted using the PRISMA method, incorporating both qualitative and quantitative analyses. The quantitative analysis identifies prevalent patterns and emerging trends in energy efficiency optimization within the LBP domain. Concurrently, the qualitative analysis explores various aspects of existing studies, including configurations of lines, managerial considerations, objectives, solution methodologies, and real-world applications. This review synthesizes current knowledge and highlights potential avenues for future research, underlining the importance of energy efficiency in driving sustainable practices in Industry 4.0 and the emerging Industry 5.0 paradigm.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"205 ","pages":"Article 111144"},"PeriodicalIF":6.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904090","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}

{"title":"System-Wide Optimization of Free-Floating Bike-Sharing for Urban Rail Stations: A demand prediction and scheduling approach","authors":"Jinjun Tang ,&nbsp;Maoxin Ren ,&nbsp;Ziyue Yuan ,&nbsp;Jianming Cai ,&nbsp;Yunyi Liang","doi":"10.1016/j.cie.2025.111121","DOIUrl":"10.1016/j.cie.2025.111121","url":null,"abstract":"<div><div>Free-floating bike-sharing (FFBS) addresses the first/last mile challenges in urban rail transit (URT), while facing supply–demand imbalance problems owing to unrestricted bike parking. Previous research primarily equated actual bike usage with demand and focused on cost-efficiency, which overlooks unmet demand and system-wide optimization. This study proposes a comprehensive framework to optimize FFBS availability at URT stations, particularly during peak hours, through 1) demand prediction, 2) time-based scheduling, 3) priority scheduling strategy, and 4) system-wide optimization. The proposed method incorporates URT ridership as a pivotal feature to enhance the accuracy of bike-sharing demand prediction in URT transfer scenarios. To achieve bike-scheduling benefits, this study introduces a grid-based approach to convert ride data into predictive orders for bike scheduling, measuring time savings across transit modes. Additionally, a prioritization strategy for bike redistribution is designed based on the classification of bus routes around URT stations, ensuring a balanced integration of FFBS and other public transport modes. A multi-objective optimization model is designed to minimize operating costs and maximize passenger time savings, which is addressed with the NSGA-III algorithm. A numerical study using Shenzhen’s public transportation data reveals that prioritizing selected stations leads to a 19.4% greater average time savings per order compared to non-priority stations, along with a 7.60% reduction in total passenger travel time. This study more accurately reflects the actual demand, thereby achieving the supply–demand balance in URT-BBS transfers.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111121"},"PeriodicalIF":6.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864664","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}

{"title":"Reliability and optimal age-based replacement policy for consecutive 2-out-of-n:G system equipped with protection blocks","authors":"Serkan Eryilmaz","doi":"10.1016/j.cie.2025.111120","DOIUrl":"10.1016/j.cie.2025.111120","url":null,"abstract":"<div><div>This paper concerns the reliability evaluation and optimal age-based replacement policy for the linear consecutive 2-out-of-<span><math><mi>n</mi></math></span>:G system whose two consecutive components are protected by a block that has its own failure rate. Two alternative methods are proposed to compute the reliability of the system. The first method is based on direct probabilistic approach and uses the reliability of the ordinary consecutive 2-out-of-<span><math><mi>n</mi></math></span>:G system. The second method is based on the concept of survival signature. Closed form equations for the system reliability and the mean number of failed components within the system are obtained. The optimal age-based replacement policy is also defined and studied. Extensive numerical results are presented to illustrate the findings.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111120"},"PeriodicalIF":6.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869591","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}

{"title":"An inter-subgroup compensation mechanism by Nash bargaining game for managing non-cooperative behavior in group decision making","authors":"Jie Yang ,&nbsp;Jian Wu ,&nbsp;Francisco Chiclana ,&nbsp;Mingshuo Cao ,&nbsp;Ronald R. Yager","doi":"10.1016/j.cie.2025.111114","DOIUrl":"10.1016/j.cie.2025.111114","url":null,"abstract":"<div><div>Non-cooperative behavior exhibited by DMs when they must make excessive interest compromises hinders the achievement of group consensus. This study develops an inter-subgroup compensation mechanism using the Nash bargaining game under the minimum cost consensus model (MCCM) framework to managing non-cooperative behavior. First, a cooperative acceptability index (CAI) based on compromise limit costs is proposed to objectively identify non-cooperative behavior. By quantifying the acceptable compromise limit costs, the CAI ensures that consensus adjustments remain within acceptable bounds. Then, an inter-subgroup compensation mechanism is designed using the Nash bargaining game from the perspective of Kaldor–Hicks improvement. This mechanism enables cooperative DMs to incentivize non-cooperative peers via resource transfers, achieving dual optimization by minimizing collective costs and ensuring individual acceptability. Finally, a community renewal application example and comparison analysis are provided to illustrate the efficacy of the proposed approach.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111114"},"PeriodicalIF":6.7,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864663","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}