Computers & Industrial Engineering最新文献

{"title":"Joint optimization of vending machine deployment and shelf display design with synchronized merchandise replenishment","authors":"Kung-Jeng Wang ,&nbsp;Natalia Febri","doi":"10.1016/j.cie.2026.111848","DOIUrl":"10.1016/j.cie.2026.111848","url":null,"abstract":"<div><div>Vending machines (VMs) serve as an important aspect of automated retail, delivering both flexibility in operations and convenience for consumers. However, as VM networks expand, managers face growing logistical challenges in determining optimal deployment locations, product selection and allocation, and restocking schedules. This study proposes a novel bi-layer optimization framework that jointly optimizes deployment, product selection and allocation, and a synchronized replenishment cycle. To address the complexity of this large-scale combinatorial problem, we develop a hybrid Tabu Search and Evolution Strategy (TS-ES) algorithm. Extensive experiments show that the synchronized replenishment cycle yields better performance than the independent cycle. Comparative analysis demonstrates that the hybrid TS-ES algorithm consistently achieves higher objective values than standalone TS, genetic algorithm (GA), random search (RS), and iterative local search (ILS) across various problem scales. This research contributes to the current body of knowledge by introducing a comprehensive framework that improves VM operational performance and serves as a practical resource for optimizing the logistics and profitability within VM networks.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111848"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081469","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":"Data-driven departure time and traffic assignment model for intercity multimodal transport system","authors":"Di Huang,&nbsp;Ziyu Liu,&nbsp;Tianle Li,&nbsp;Ziyuan Gu","doi":"10.1016/j.cie.2026.111834","DOIUrl":"10.1016/j.cie.2026.111834","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111834"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081470","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 rolling horizon based bi-objective optimization approach for dynamic truck dispatching with cross-dock door assignment","authors":"Xinghan Chen ,&nbsp;Yuzhilin Hai ,&nbsp;Maoxiang Lang","doi":"10.1016/j.cie.2026.111826","DOIUrl":"10.1016/j.cie.2026.111826","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111826"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081471","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":"Competing for the most profitable tour: the orienteering interdiction game","authors":"Eduardo Álvarez-Miranda ,&nbsp;Markus Sinnl ,&nbsp;Kübra Tanınmış","doi":"10.1016/j.cie.2026.111900","DOIUrl":"10.1016/j.cie.2026.111900","url":null,"abstract":"<div><div>The orienteering problem is a well-studied and fundamental problem in transportation science, where we are given a graph with prizes on the nodes and lengths on the edges, together with a budget on the overall tour length. The goal is to find a tour that respects the length budget and maximizes the collected prize. In this work, we introduce the orienteering interdiction game, which finds various applications such as political campaign management and identification of important locations for patrolling. In this game, a competitor (the leader) tries to minimize the total prize that the follower can collect within a feasible tour. To this end, the leader interdicts some of the nodes so that the follower cannot collect their prizes. The resulting interdiction game is formulated as a bilevel optimization problem, and a single-level reformulation is obtained based on interdiction cuts. A branch-and-cut algorithm with several enhancements, including the use of a tour pool, a cut pool and a heuristic method for the follower’s problem, is proposed. In addition to this exact approach, a genetic algorithm is developed to obtain high-quality solutions in a short computing time. In a computational study based on instances from the literature for the orienteering problem, the usefulness of the proposed algorithmic components is assessed, and the branch-and-cut and genetic algorithms are compared in terms of solution time and quality.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111900"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190215","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 two-stage stochastic programming model for the location-inventory problem in multi-period closed-loop leased pallet pooling systems","authors":"Xiangling Hu ,&nbsp;Ying Dai ,&nbsp;Fei Yang ,&nbsp;Zujun Ma","doi":"10.1016/j.cie.2026.111894","DOIUrl":"10.1016/j.cie.2026.111894","url":null,"abstract":"<div><div>In the pallet leasing industry, a well-designed logistics system ensures high service levels while reducing operating costs. This study addresses an integrated facility location and inventory control problem with stochastic demand and returns in a multi-period closed-loop leased pallet pooling system (LPPS). Special consideration is given to cyclic inventory in both forward and reverse flows, as well as different levels of operation centers (OCs), and the limited repair capacity of these centers. The problem is formulated as a two-stage stochastic programming model and solved using the sample average approximation method. The results of numerical experiments indicate that the quality of returned pallets has a significant impact on LPPS design, while the type of stochastic demand has a minimal effect on strategic decisions but a considerable impact on tactical decisions. The impacts of model parameters on optimal decisions are also analyzed, and corresponding managerial implications are provided.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111894"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190364","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 Data-Driven Multi-Objective optimization framework for dynamic job shop scheduling with order Acceptance, inventory and Energy-Aware decisions","authors":"Amir Hossein Akbari ,&nbsp;Mostafa Jafari ,&nbsp;Peyman Akhavan","doi":"10.1016/j.cie.2026.111886","DOIUrl":"10.1016/j.cie.2026.111886","url":null,"abstract":"<div><div>In the modern manufacturing environment, companies face increasing pressure to balance production efficiency, energy consumption, and customer satisfaction amid dynamic operational challenges. This study addresses these challenges by proposing a novel dynamic job shop scheduling problem (DJSSP) model that integrates order acceptance and rejection decisions, machine deterioration, energy consumption, and raw material inventory management. Orders arrive dynamically and must be accepted or rejected in real time, each characterized by specific processing times, revenues, due dates, and tardiness costs. Machines operate at variable speeds, each associated with distinct energy consumption profiles and deterioration rates, while maintenance restores machine performance at the expense of downtime. The model aims to maximize profit and the number of accepted orders while minimizing energy consumption, reflecting both economic and environmental objectives. A hierarchical metaheuristic approach combining a multi-objective genetic algorithm and data mining techniques is developed to efficiently solve the problem. The applicability and effectiveness of the model are demonstrated through a case study in a stone paper factory and comparison with existing literature. The results indicate the superiority of the proposed method over alternative approaches. Specifically, the proposed method accepts 8.02% more orders and reduces energy consumption by 18.79% compared to the real-world system, while profit decreases by only 5.61%. When considering the second objective function alone, the number of accepted orders increases by 12.33% with only a 5.03% reduction in profit, highlighting its critical role in decision-making. Machine availability under the proposed method is higher than in other approaches and the real-world scenario, reaching 88.62%. Effective raw material management reduces ordering costs by 14% and lowers energy consumption by an average of 3.06%. Furthermore, ignoring machine deterioration can significantly impact system performance, causing an 11.7% reduction in profit, a 9.6% decrease in accepted orders, and a 9.8% increase in energy consumption, demonstrating that failure to account for deterioration can lead to major deviations in production planning.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111886"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190366","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":"On planning cost-efficient and flexible aircraft maintenance operations: Technician shift scheduling and task assignment over multiple bases","authors":"José Ignacio Sanhueza ,&nbsp;Felipe Delgado ,&nbsp;Mathias A. Klapp","doi":"10.1016/j.cie.2026.111801","DOIUrl":"10.1016/j.cie.2026.111801","url":null,"abstract":"<div><div>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.</div><div>We study how a maintenance provider should decide where (<em>i.e.</em>, at which base), when (<em>i.e.</em>, within each aircraft’s ground-time window), and by whom (<em>i.e.</em>, 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 (<em>i.e.</em>, assigning different shift start times to technicians across workdays), and spatial flexibility (<em>i.e.</em>, relocating technicians among maintenance bases).</div><div>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.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111801"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146045176","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":"Optimizing buffer management strategies for engineer-to-order project supply chains in uncertain environments","authors":"Junguang Zhang ,&nbsp;Xi Wang ,&nbsp;Estrella Díaz","doi":"10.1016/j.cie.2026.111870","DOIUrl":"10.1016/j.cie.2026.111870","url":null,"abstract":"<div><div>Engineer-to-Order (ETO) project supply chains exhibit heightened operational complexity due to product customization, geographically dispersed supplier networks, and demand uncertainty. While existing studies have validated the risk-mitigation value of safety stock and time buffers, two critical gaps persist at the micro-operational level: (1) the absence of refined configuration methods for node-specific buffer parameters, and (2) the pressing need for dynamic adjustment mechanisms responsive to real-time disruptions. We propose a cascading risk-driven dynamic buffer management framework for supply chains. First, a multidimensional cascading risk quantification index system is developed, which integrates edge load and risk perception dimensions to precisely identify and quantify risk propagation effects, thereby enabling optimal node-level buffer strategy design. Second, a real-time monitoring-based cross-node buffer resource coordination mechanism is created, enhancing system resilience through dynamic adjustments in buffer capacity and allocation. The simulation results demonstrate that this approach can improve on-time delivery performance and reduce supply chain costs. This research provides a decision support tool for ETO project supply chains to dynamically balance operational resilience and cost efficiency in uncertain environments.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111870"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190487","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 scenario-adaptive optimization model for circular intertwined supply network design under uncertainty","authors":"Mohaddeseh Roshan ,&nbsp;Jessica Olivares-Aguila ,&nbsp;Waguih ElMaraghy","doi":"10.1016/j.cie.2026.111849","DOIUrl":"10.1016/j.cie.2026.111849","url":null,"abstract":"<div><div>Intertwined supply networks are collaborative, cross-industry supply chains characterized by a high level of interconnectedness among their entities. This study demonstrates that integrating circular economy principles into such networks can cut greenhouse gas emissions by 4.97% and reduce total system costs by 11.03%, while strengthening economic efficiency and social responsibility under uncertainty. To realize these improvements, a novel multi-objective non-linear mixed-integer mathematical model is proposed with an embedded scenario differentiation mechanism that enables evaluation of configurations, from traditional decentralized supply chains to complex intertwined networks with varying levels of circularity, within a unified analytical model. The objective functions are to minimize system costs and greenhouse gas emissions and maximize social responsibility for optimal location decisions under uncertainty. The proposed model is first verified using the AUGMECON-2 method and validated via a case study of an intertwined pharmaceutical-bioplastic supply network, complemented by numerical experiments, sensitivity analyses, and a comparative study using the Grey Wolf Optimizer for large-scale instances.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111849"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081472","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":"Research on the digital transformation strategies and behavioral selection in consumer-driven digital ecosystem","authors":"Daoping Wang ,&nbsp;Cancan Liu ,&nbsp;Ruifang Shen","doi":"10.1016/j.cie.2026.111893","DOIUrl":"10.1016/j.cie.2026.111893","url":null,"abstract":"<div><div>In digital ecosystems, consumers have evolved from passive end-users to essential participants in production and value co-creation. Collaboration between consumers, small and medium-sized enterprises (SMEs), and leading industry enterprises is a crucial factor in the digital transformation of industries. However, SMEs have undermined the effectiveness of industrial chain collaboration in their digital transformation because they lack resources and expertise, as well as a lack of strategic vision. The purpose of this research is to investigate how players in consumer-driven digital ecosystems are implementing digital transformation techniques and how government subsidies affect behavioral choice tactics. This study constructs a differential game model to solve for the optimal pricing levels, co-innovation effort levels, digital transformation levels, and industrial chain profits under various cooperation intensities and behavioral choice patterns, as well as to analyze the impact of key parameters on optimal decisions, digital transformation, and member behavior choices. The main research findings indicate that cooperative decision-making significantly improves the level of industrial digitalization and the total profit of the system, unleashing the multiplier effect of collaborative innovation; myopic behavior has a significant inhibitory effect on supply chain development, with the myopia of leading enterprises having a more obvious negative impact; consumer demand and policy incentives are key driving factors for digital transformation, The findings offer theoretical insights into digital transformation and consumer behavior within digital ecosystems.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"214 ","pages":"Article 111893"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146190214","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}