Computers & Industrial Engineering最新文献

{"title":"Location-routing problem for customized product delivery considering assembly delay","authors":"Mengrui Liu ,&nbsp;Nengmin Wang ,&nbsp;Meng Zhang ,&nbsp;Weixuan Shi","doi":"10.1016/j.cie.2025.111086","DOIUrl":"10.1016/j.cie.2025.111086","url":null,"abstract":"<div><div>The delivery of assemble-to-order (ATO) products differs from that of standard products because the assembly process begins after receiving customer orders. As both assembly and distribution work have recently been outsourced to third-party logistics (3PL), the resulting preparation time gap between ATO and standard products imposes new time constraints on 3PL operations. To optimize delivery strategies and minimize total costs for 3PL providers under the new condition, this study addresses the location-routing problem for customized product delivery considering assembly delay (CPADLRP), which determines the location strategy of forward assembly warehouses and distribution strategy of ATO products simultaneously. We formulate the problem as a mixed-integer programming model, incorporating a novel variation of time window constraints with dynamically changing start time boundaries. An improved adaptive large neighborhood search (ALNS*) algorithm is proposed to solve this problem, incorporating a principal-component-analysis-based k-means and four problem-specific operators to the basic ALNS. Compared with the Gurobi Solver and two other typical heuristic algorithms, ALNS* achieves better solutions more efficiently. Moreover, we conduct a series of sensitivity analyses on the main factors of the problem and drive several managerial insights for 3PL providers to reduce total costs. The sensitivity analysis on the proportion of customized orders also verifies the importance of considering the assembly delay in the LRP.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111086"},"PeriodicalIF":6.7,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826298","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 remanufacturing operations: A review on Decision-Making models and their implementation challenges","authors":"Mario Caterino ,&nbsp;Raffaele Iannone ,&nbsp;Roberto Macchiaroli ,&nbsp;Stefano Riemma ,&nbsp;Duc Truong Pham ,&nbsp;Marcello Fera","doi":"10.1016/j.cie.2025.111088","DOIUrl":"10.1016/j.cie.2025.111088","url":null,"abstract":"<div><div>This paper reviews operational decision-making models and tools in the field of remanufacturing. Past research on this subject highlighted a predominance of strategic and tactical decision tools. However, operational decision-making represents an open issue for the remanufacturing process. For this reason, this review employs a systematic methodology to update existing literature surveys, evaluate the recent advancements made on the subject, and identify the main barriers that limit the application of existing models in real industrial remanufacturing contexts. The results highlight significant advancements in decision-support tools, particularly in the inspection and disassembly phases, where modern technologies, such as machine learning and robotics, can enhance decision-making processes. Despite these advancements, several barriers to the industrial implementation of existing models persist, mainly related to the availability of data for their application. This often leads to other sub-problems, such as the omission of uncertainties typical of the remanufacturing process. The paper concludes by analysing potential future research trends in this area, emphasising the necessity of systems that gather and utilise data for decision-making across all remanufacturing phases. A preliminary proposal for such a system is presented.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111088"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814920","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 efficient matheuristic integration with benders decomposition for unmanned aerial vehicle routing problem in forest fire surveillance","authors":"İhsan Sadati","doi":"10.1016/j.cie.2025.111087","DOIUrl":"10.1016/j.cie.2025.111087","url":null,"abstract":"<div><div>Wildfires annually cause extensive and immeasurable harm to the environment, incurring significant costs for containment efforts. Early detection plays a crucial role in preventing the escalation of wildfires, requiring accurate and frequent updates on images and information. Despite advancements in detection methods utilizing image processing and satellite monitoring, the demand for improved precision and frequency persists. Presently, satellite images can detect fires as small as 0.1 ha with an accuracy of 1 km. While helicopters offer detailed information, their use is both hazardous and expensive. There is growing interest in Unmanned Aerial Vehicles (UAVs) for wildfire detection due to their ability to quickly cover potential fire areas using high-definition and thermal infrared cameras, particularly in remote and hazardous terrains. This study addresses the routing and scheduling of UAVs for forest fire surveillance. A mixed-integer linear programming (MILP) model is formulated, followed by the introduction of matheuristic approaches to tackle and solve the problem, drawing inspiration from variable neighborhood search. Matheuristics, which integrate mathematical programming techniques and heuristics, provide efficient optimization methods. Additionally, we incorporate Benders Decomposition to enhance the optimization process by decomposing the problem into a master problem and a subproblem, allowing for more effective exploration of feasible solutions. To evaluate the effectiveness of our proposed solution approach, computational experiments are conducted using a set of instances generated from the Covering Vehicle Routing Problem (CoVRP) and Electric Vehicle Routing Problem (EVRP) datasets. The results indicate that our proposed matheuristics approach, augmented by Benders Decomposition, is capable of producing high-quality solutions. Furthermore, a case study is presented focusing on the Belgrade Forest, one of the largest forests in Istanbul, Turkey, to underscore the benefits of utilizing UAVs in forest fire surveillance.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111087"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869590","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":"Does blockchain-enabled quality inspection work better in hybrid retailing?","authors":"Cuihua Zhang ,&nbsp;Xiufang Li ,&nbsp;Henry Xu ,&nbsp;Zhitang Li ,&nbsp;Xiangru Zhao","doi":"10.1016/j.cie.2025.111092","DOIUrl":"10.1016/j.cie.2025.111092","url":null,"abstract":"<div><div>The development of e-commerce platforms has driven brand owners to expand their markets through hybrid retailing, i.e., the cooperation of an incumbent seller and an agent seller to sell products. However, achieving effective quality control remains a significant challenge for brand owners. Compared with conventional quality inspection (CQI), blockchain-enabled quality inspection (BQI) is a promising solution to address quality control issues such as inspection errors and the invisibility of production processes. The main objective of this paper is to investigate how to make an optimal strategy choice between BQI and CQI. We consider a supply chain involving a supplier and a brand owner and take a game-theoretic approach to analyze the two players’ preferences for quality control strategies and the impact of hybrid retailing on their strategy preferences. The results suggest that when the quality cost coefficient is small, the quality of the components will be high or even perfect. In this case, the brand owner should implement the no-inspection policy under the CQI strategy. When the quality cost coefficient is at a medium level, the brand owner can choose the BQI strategy to avoid, to a certain extent, the supplier’s strategic input quality decision-making behavior. Moreover, as the quality cost coefficient rises, the external failure cost increases, or the blockchain adoption cost decreases, the BQI strategy is more favorable to the supplier and the brand owner than the CQI strategy. Furthermore, introducing hybrid retailing benefits the supplier and the brand owner when the market size of the external sales platform is large. However, introducing hybrid retailing increases the supplier’s and brand owner’s preference for the no-inspection policy and reduces their preference for the full-inspection policy and the BQI strategy. Our research findings provide guidance for brand owners and suppliers to choose appropriate quality control strategies and offer a theoretical basis for them to make quality and pricing decisions in actual operations.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111092"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814810","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":"Similarity based fuzzy TOPSIS with OWA: Reflecting risk attitudes in multiple-criteria and multi-expert evaluation under uncertainty","authors":"Pasi Luukka ,&nbsp;Jan Stoklasa","doi":"10.1016/j.cie.2025.111081","DOIUrl":"10.1016/j.cie.2025.111081","url":null,"abstract":"<div><div>We present similarity based fuzzy Technique for Order of Preferences by Similarity to Ideal Solution (fTOPSIS) using ordered weighted averaging (OWA) operators. With OWA operators we extend the use of similarity based fTOPSIS in two ways. First in several types of real world engineering decision making problems the amount of criteria required to be satisfied to a high extent is more important than satisfying particular criteria; also in the aggregation of expert evaluations the amount of experts providing good/bad evaluations might be critical. This kind of generalization is now made possible by using OWA in the proposed method. Second by using linguistic quantifiers to define weights for OWA and allowing different quantification for the similarity to Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS) we allow decision-maker’s risk preference to be reflected. This allows us to model risk-averse or risk-seeking decision making in fTOPSIS for the first time. Aggregation of multiple expert evaluations using fTOPSIS that considers specific linguistically expressed risk-attitude of the user of the final evaluation is now also enabled in fTOPSIS. The advantage of the proposed method lies in the ability to adjust the method according to decision makers’ risk preferences. Multiple expert evaluations can also now be aggregated according to the end-user’s risk preference. The proposal enables separate treatment of FPIS and FNIS using OWA operators to reflect decision maker’s optimism/pessimism. Presented findings show that by doing this we are able to reflect risk attitudes and receive different ranking corresponding with risk preferences.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111081"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814811","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":"Identifying and evaluating R&D partners via patent-based multilayer networks from the perspective of knowledge complementarity: A case study of unmanned ship technology","authors":"Jinfeng Wang ,&nbsp;Ningtao Wang ,&nbsp;Weiyu Zhao ,&nbsp;Lijie Feng","doi":"10.1016/j.cie.2025.111085","DOIUrl":"10.1016/j.cie.2025.111085","url":null,"abstract":"<div><div>With the rapid pace of technological development, innovation is crucially related to cross-disciplinary collaboration and resource sharing. To address this challenge, researchers need to break existing knowledge boundaries by seeking potential collaborations. However, when identifying and evaluating partners, existing studies have failed to explore patent technology information, patent citation information, and the complex collaborative relationships among patent holders. This results in an incomplete and inaccurate identification and evaluation of potential R&amp;D partners. In response, this study proposes a multilayer network framework based on patent data to identify and evaluate potential R&amp;D partners. This framework considers patent technical information, citation information, and collaboration among patentees. The method consists of three key stages. First, a network of collaboration between patentees, a knowledge network, and a patent citation network are constructed. Second, complementarity metrics are proposed on the basis of the combination of similarity and heterogeneity to identify potential R&amp;D partners. Finally, potential R&amp;D partners are further evaluated and determined by analyzing competitive or collaborative relationships. The proposed method is verified through a case study of unmanned ship technology. This method provides a more comprehensive perspective for R&amp;D partner identification and evaluation. Moreover, the results provide a reference for enterprises to improve their collaboration efficiency.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111085"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821172","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":"A stochastic optimization model and decomposition techniques for surgery scheduling with duration and emergency demand uncertainty","authors":"Xiaoyue Gong ,&nbsp;Jian-Jun Wang ,&nbsp;Hongru Miao ,&nbsp;Lejing Yu ,&nbsp;Zhili Liu","doi":"10.1016/j.cie.2025.111096","DOIUrl":"10.1016/j.cie.2025.111096","url":null,"abstract":"<div><div>A robust and reasonable ex-ante operating rooms (ORs) scheduling for the upcoming surgery day is important as it provides a fundamental reference for equipment management and a working plan for staff physicians. This study aims to develop effective initial OR schedules in the presence of stochastic duration and emergency demand where elective and emergency demand share open multi-functional ORs in a specialty. In addition, physicians’ precedence requirements are considered to ensure that the resulting schedule facilitates the smoothness of each physician’s work under any uncertainty realization. Through characterizing the duration and emergency demand uncertainties by a scenario set, a two-stage stochastic optimization model is formulated to minimize the total expected costs under uncertainties. An effective decomposition algorithm is developed, given that the simpler variant of this problem is known as NP-hard. Several enhancements were added based on the understanding of the proposed problem and the established model. Numerical results highlight the benefits of considering both uncertainties when curating initial OR schedules. The effectiveness of the proposed algorithm and its significant advantage over the commercial solver in terms of efficiency are demonstrated. Finally, to obtain good feasible schedules within a desirably short time, a Monte-Carlo sampling approximation based on our decomposition algorithm is also proposed and its effectiveness is briefly demonstrated.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111096"},"PeriodicalIF":6.7,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814752","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":"A continual learning approach for failure prediction under non-stationary conditions: Application to condition monitoring data streams","authors":"M.A. Benatia ,&nbsp;M. Hafsi ,&nbsp;S. Ben Ayed","doi":"10.1016/j.cie.2025.111049","DOIUrl":"10.1016/j.cie.2025.111049","url":null,"abstract":"<div><div>Accurate forecasting of Remaining Useful Life (RUL) is crucial for predictive maintenance (PdM), permitting prompt actions that decrease downtime and maintenance expenses. Yet, conventional RUL estimation techniques often struggle to adjust to changing operational conditions and data drift, restricting their use in dynamic industrial settings. This research presents a continual learning framework designed for these non-stationary conditions, where models progressively learn from new data while retaining previously gained insights. By tackling issues such as catastrophic forgetting, the proposed technique enhances robustness and adaptability, rendering it applicable to real-world scenarios. The framework’s efficacy is validated using realistic industrial scenario datasets, like AI4I and N-CMAPSS, which include varied scenarios such as manufacturing and aerospace operations. Experimental findings showcase significant enhancements in prediction accuracy and model resilience over traditional methods. Incorporating deep neural network architectures, such as Multi-Layer Perceptrons (MLP) and Convolutional Neural Networks (CNN), within the continual learning paradigm, optimizes performance for dynamic data shifts. This study advances RUL estimation methods by offering a scalable and practical solution for PdM in sectors where reliability and efficiency are paramount. Its capacity to adapt to evolving operational conditions and provide actionable insights bolsters improved maintenance strategies, curtailing unexpected disruptions and operational costs. The proposed framework is particularly beneficial for sectors like manufacturing, energy, and aerospace, where non-stationary data and evolving failure modes present significant challenges.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111049"},"PeriodicalIF":6.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814751","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 improved adaptive fuzzy-genetic algorithm based on local search for integrated production and mobile robot scheduling in job-shop flexible manufacturing system","authors":"Erlianasha Samsuria ,&nbsp;Mohd Saiful Azimi Mahmud ,&nbsp;Norhaliza Abdul Wahab ,&nbsp;Muhammad Zakiyullah Romdlony ,&nbsp;Mohamad Shukri Zainal Abidin ,&nbsp;Salinda Buyamin","doi":"10.1016/j.cie.2025.111093","DOIUrl":"10.1016/j.cie.2025.111093","url":null,"abstract":"<div><div>The central focus of this paper is to generate optimal schedules for job operations using mobile robots with the lowest makespan in a Flexible Manufacturing System (FMS). In Job-Shop FMS, specific machines are selected for individual jobs which requires higher levels of flexibility and complexity in scheduling. The joint scheduling problem in a Job-Shop FMS primarily involving the coordination of the production machines and mobile robots in schedules. Genetic Algorithm (GA) has emerged as the most extensively implemented evolutionary algorithm to address the production scheduling due to its capability to produce high-quality, rapid, and efficient results in exploring complex and global solution spaces. Despite its strong global search capability, the algorithm is prone to trap in its local optima when tackling the complex problem of scheduling mobile robots in a job-shop setting with precedence constraints. Therefore, this paper presents an improved structure of GA by integrating it with adaptive Fuzzy-GA operators and Tabu Search (TS) algorithm to minimize the makespan. The resulting hybrid algorithm offers a novel approach that effectively balances search performance to achieve high-quality solutions in terms of fitness minimization and convergence speed. The proposed algorithm was tested using several benchmark datasets and was subjected to comparative experimental analysis. The empirical results demonstrate the improvement of the proposed algorithm over comparative methods, with improvements of 6.5%, 6.9% and 9.8% over the GA-Tabu algorithm, Fuzzy-GA, and standard GA respectively, in solving the complex scheduling problem within FMS.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111093"},"PeriodicalIF":6.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844813","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":"Construction of a new robust dual-channel supply chain network with forward logistics and reverse logistics","authors":"Qianxue Zhang ,&nbsp;Hongliang Li ,&nbsp;Huili Pei ,&nbsp;Naiqi Liu","doi":"10.1016/j.cie.2025.111075","DOIUrl":"10.1016/j.cie.2025.111075","url":null,"abstract":"<div><div>Dual-channel closed-loop supply chain (CLSC) is a new supply chain model that integrates the offline and online sales channels into a CLSC. Dual-channel CLSC involves more echelons, which often leads to uncertainty in the dual-channel CLSC design. Although some studies have focused on uncertain dual-channel CLSC designs, there are still research gaps in the existing literature, such as a lack of robust models, inefficiencies in existing designs, and limited attention to certain industries. To fill these research gaps, we examine the design of the CLSC network based on partially known distribution information about uncertain transportation costs and demand. We construct a moment ambiguity set for uncertain costs and a bounded unimodal ambiguity set for uncertain demand. Using these ambiguity sets, we develop a new distributionally robust optimization (DRO) model with ambiguous chance constraints (ACCs) for the dual-channel CLSC design problem, which can be reformulated as a computationally tractable mixed-integer linear programming (MILP) model. To enhance solving efficiency, we build an accelerated Benders decomposition (BD) algorithm for the MILP model. A case study on BYD automotive illustrates the effectiveness of our developed approach. The computational results demonstrate that our proposed model withstands uncertainties in transportation costs and demand with a probability of 95%, establishing a dual-channel CLSC network that balances robustness and cost-effectiveness, resulting in a total cost reduction of approximately 14% compared to the deterministic model. Additionally, the sensitivity analysis reveal that the adjustment of the ACC tolerance level, the proportion of online and offline sales, and the handling methods of products significantly influence BYD Auto.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111075"},"PeriodicalIF":6.7,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}