Transportation Research Part E-Logistics and Transportation Review最新文献

{"title":"Multi-objective double-floor corridor allocation problem with floor loads and separated passages","authors":"Dan Ji ,&nbsp;Zeqiang Zhang ,&nbsp;Wei Liang ,&nbsp;Zihan Guo ,&nbsp;Zongxing He","doi":"10.1016/j.tre.2025.104453","DOIUrl":"10.1016/j.tre.2025.104453","url":null,"abstract":"<div><div>Current research on multi-floor stereoscopic workshop layouts disregards the effects of floor load constraints and interference with the workers and logistics, which lead to low productivity and escalating transportation risks. This study examines a double-floor corridor allocation problem considering floor loads and separated worker-logistics transportation passages (DFCAP_FLSP). To this end, a mixed-integer programming model involving constraints on facility allocation, multi-type transportation distance computation, and floor loading is constructed to minimize material handling costs, employee walking distances, and floor loading gaps. Subsequently, a multi-objective self-learning memetic algorithm (MOSLMA) is developed to solve the DFCAP_FLSP efficiently. The algorithm employs linear programming to achieve two-stage decoding and utilizes Q-learning to improve local search performance. Comparison experiments conducted with the genetic algorithm, multi-objective particle swarm optimization, and non-dominated sorting genetic algorithm II for the four benchmark instances reveal that MOSLMA achieved the highest percentages of non-inferior solutions close to the Pareto solution (68.75%, 93.18%, 100%, and 87.5%), highlighting its advantages. Finally, the proposed layout and algorithm are applied to the reducer manufacturing workshop, and the scheme comparison indicates the superiority of the proposed layout structure in safety and cost-effectiveness.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104453"},"PeriodicalIF":8.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220353","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 autonomous multimodal last-mile delivery systems with time windows: Analyzing trade-offs between drones, robots, and trucks","authors":"Giovanni Campuzano,&nbsp;Eduardo Lalla-Ruiz,&nbsp;Martijn Mes","doi":"10.1016/j.tre.2025.104427","DOIUrl":"10.1016/j.tre.2025.104427","url":null,"abstract":"<div><div>This paper studies multi-modal last-mile delivery systems. More specifically, it introduces the Drone-Assisted Vehicle Routing Problem with Robot Stations and Time Windows (VRPD-RS-TW) to face exigent delivery schedules in last-mile logistics. The VRPD-RS-TW applies to highly populated city centers, where due to infrastructural issues, customers might be hard to reach by conventional trucks. This problem is characterized by utilizing three transportation modes: trucks, drones, and robots collaborating to deliver parcels and meet time window requirements. To solve this problem, we develop a Mixed Integer Linear Programming (MILP) formulation, valid inequalities to strengthen the linear relaxation, and a Three-Phased Granular Multi-Start Iterated Local Search (3P-GMS-ILS) metaheuristic algorithm. A computational study on instances of Amsterdam (the Netherlands) demonstrates that the 3P-GMS-ILS outperforms the MILP formulation and state-of-the-art metaheuristic approaches in terms of both objective function values and computational times. Furthermore, we provide insights into the effectiveness of the VRPD-RS-TW, showing that, under various cost scenarios, the combination of trucks, drones, and robots outperforms scenarios with fewer transportation modes. Across the studied cost scenarios, the VRPD-RS-TW simultaneously coordinates a higher volume of delivery operations, with 48.75 % performed by drones and robots, resulting in better objective function values than the related transportation systems. In scenarios where truck routing costs are lower than those of drones and robots, the VRPD-RS-TW still achieves better objective function values compared to the related transportation systems, although the share of drone and robot deliveries drops to 14.78 %. This shows that adding drones is not necessarily beneficial when trucks carry drones, as trucks should wait for drones, which might result in higher costs related to drone routing and drivers’ wages.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104427"},"PeriodicalIF":8.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220354","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":"Joint optimization of slot and empty container co-allocation for liner alliances with uncertain demand in maritime logistics industry","authors":"Shaorui Zhou ,&nbsp;Xiaorui Liu ,&nbsp;Jihong Chen ,&nbsp;Min Zhao ,&nbsp;Fan Wang ,&nbsp;Lingxiao Wu","doi":"10.1016/j.tre.2025.104437","DOIUrl":"10.1016/j.tre.2025.104437","url":null,"abstract":"<div><div>With the growth traffic of containerized shipping worldwide, container liners have seen increasing cooperation. Slot co-allocation has drawn wide attention as a way of cooperation within liner alliances. However, due to the need for liner alliances to predict uncertain future demands to formulate empty container scheduling plans, empty container repositioning and co-allocation are essential but seldom considered. In response to this, this paper jointly optimizes the slot and empty container co-allocation issues by considering slot and empty container sharing. First, we proposed a two-stage stochastic programming model to minimize the total cost of the liner alliance. To solve the high-dimensional stochastic programming problem, we then proposed two new hybrid stochastic learning algorithms, which utilize the network structure while adaptively approximating the objective function by learning from historical data. Finally, we tested our algorithm in the real route data of the Ocean Alliance between South Asia and Southeast Asia. Computational results indicate that the proposed algorithms exhibit effective and efficient performance for joint optimization of slot and empty container co-allocation for liner alliances with uncertain demand, and some interesting managerial insights can be drawn from the rolling-horizon experiments.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104437"},"PeriodicalIF":8.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220350","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":"Parking preferences of delivery drivers in the Paris Region: Understanding the role of anticipation using hybrid choice models","authors":"Romain Crastes dit Sourd ,&nbsp;Pascal Gastineau ,&nbsp;Adrien Beziat ,&nbsp;Martin Koning","doi":"10.1016/j.tre.2025.104420","DOIUrl":"10.1016/j.tre.2025.104420","url":null,"abstract":"<div><div>This study explores the determinants of parking choices for commercial vehicles in the Paris Region (France). The analysis is based on data from the 2010 Paris Region Urban Goods Movement Survey (UGMS), which offers insights into the parking preferences of delivery drivers. By examining real-world decision-making, the dataset allows us to consider spatial and temporal characteristics as well as the role of parking decision within the delivery process. An integrated choice and latent variable model is employed, whereby drivers select parking locations based on urban environmental attributes, service type, and a latent variable reflecting anticipated delivery difficulty. This difficulty is inferred from observed delivery times and service characteristics; furthermore, temporal variations are incorporated to assess driver behavior, including fluctuations in parking preferences throughout the day. The model also accounts for parking space availability by the means of latent classes. Our findings contribute to a nuanced understanding of delivery drivers’ behavior, providing valuable insights for policy-making and operational strategies. These results, as well as our modeling approach, can also be incorporated into broader frameworks such as agent-based models.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104420"},"PeriodicalIF":8.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220413","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":"Is data sharing consistently good with AI service? Impact of data sharing and service strategies in competitive channels","authors":"Yu Bai ,&nbsp;Yang Liu ,&nbsp;Xiuwu Liao","doi":"10.1016/j.tre.2025.104383","DOIUrl":"10.1016/j.tre.2025.104383","url":null,"abstract":"<div><div>AI services based on data sharing have recently become essential for online platforms and retailers. This study examines an online platform that offers AI services to itself and its associated retailer, which competes by offering substitute products. The retailer can share data with the platform or develop alternative service channels. Our research explores the dynamic interaction between the platform’s decision to offer AI services, the retailer’s data-sharing choices, and service channel selection. Our findings reveal that data sharing can significantly enhance AI service quality and boost market demand for the platform’s AI service. However, it also creates a power imbalance between platforms and retailers. For platforms, gaining access to retailer data enhances service quality, increases demand, and boosts revenue. For retailers, data sharing creates a <em>Synergy Effect</em> that improves both price and demand and finally increases revenue. However, data sharing is not always beneficial, as the <em>Synergy Effect</em> may be inefficient or diminished because of the <em>Triple Squeeze Effect</em>, ultimately resulting in profit losses. We also analyze the role of data processing capability and find that increasing capability does not always lead to improved outcomes, particularly when high costs burden the platform. Our results indicate that choosing the platform’s service is usually more beneficial for the retailer due to the <em>Synergy Effect</em>, while the platform’s service provision strategy needs to be cautious. Our study provides valuable managerial insights, suggesting that both platforms and retailers must carefully evaluate the cost-benefit trade-offs associated with data sharing and data processing investments to ensure profitability and sustainable growth.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104383"},"PeriodicalIF":8.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220412","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":"Two-echelon container drayage with multiple transportation modes and overall-network time interdependence","authors":"Decheng Wang ,&nbsp;Xiaolan Xie ,&nbsp;Ilkyeong Moon","doi":"10.1016/j.tre.2025.104436","DOIUrl":"10.1016/j.tre.2025.104436","url":null,"abstract":"<div><div>This study addresses a two-echelon container drayage problem incorporating multiple transportation modes, and attempts to explore its potential application advantages. The problem concentrates on truckload transportation, and represents a variation of the classical two-echelon capacity-constrained vehicle routing problem. In the first echelon, a fleet of tractors, often employing long combination vehicles, transports trailers between a central depot and multiple satellites. In the second echelon, a fleet of tractors, restricted to a single-trailer stay-with mode, due to transportation regulations, executes multi-trip trailer transportation between satellites and customers. The tractor can perform two operations of dropping-off and pulling-up trailers (i.e., simultaneous delivery and collection of containers are involved). These characteristics make the routes of the two echelons couple tightly, and result in intertwined time interdependence within the entire network. A mathematical formulation is developed to address this two-echelon scheduling with time interdependence. To enhance computational efficiency, two groups of valid inequalities are provided. A two-stage matheuristic algorithm integrating the proposed mathematical model and heuristic techniques is developed. A route-string scheduling framework combined with a fixing and releasing mechanism is introduced to mitigate the complexity associated with the time-interdependence nature of the network. This algorithm, possessing fewer parameters than comparable (meta-) heuristics, offers a practical implementation. The mathematical model, along with the valid inequalities and the performance of the matheuristic algorithm, are validated through computational experiments using established instances from prior studies. Furthermore, experiments are undertaken to investigate the effects of customer distribution patterns and maximum permissible trailers count on operational efficiency.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104436"},"PeriodicalIF":8.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220414","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 charging station locations for mixed traffic of electric and gasoline vehicles: a stochastic user equilibrium approach","authors":"Bing Zeng,&nbsp;Xinlian Yu,&nbsp;Zihao Zhang,&nbsp;Ziyuan Pu","doi":"10.1016/j.tre.2025.104438","DOIUrl":"10.1016/j.tre.2025.104438","url":null,"abstract":"<div><div>Charging station (CS) location planning is critical for accommodating the growing demand of electric vehicles (EVs). This paper develops a mixed-integer nonlinear programming (MINLP) model to address the charging station location and capacity problem in the road networks with mixed traffic of electric and gasoline vehicles, aiming to minimize both charging station investment costs and travel time costs. The main contributions of this study include: i) existing studies often assume that users are perfectly rational and cooperatively choose the shortest paths under the user equilibrium framework, overlooking perception errors and the stochastic nature of route choice. Thus, this model adopts a Stochastic User Equilibrium (SUE) framework to reflect users’ imperfect perceptions and decision-making variability in mixed traffic networks. ii) Inaccurate waiting time estimates are often overlooked during charging station location planning, leading to suboptimal and costly locations. Therefore, this study incorporates EV waiting time into the location decision and proposes a machine learning-based estimation model to improve prediction accuracy. Furthermore, this study proves the uniqueness of the SUE pattern through theoretical derivation, facilitating the joint application of the sparrow search algorithm, path-based method of successive averages, and random forest model to solve the MINLP. A case study is conducted on networks of varying sizes. Results from a realistic Eastern-Massachusetts highway network demonstrate that the accuracy of waiting time predictions will impact CS location-capacity results. Compared to the UE-based charging station location model, the SUE-based model produces a more dispersed traffic flow and less congestion on the shortest routes by integrating user perception errors and preference heterogeneity, thereby reducing travel time cost by 49.08% and total system cost by 48.83%. This study provides practical value for EV CS planning by addressing user perception errors and real-time waiting time prediction. Future research includes considering dynamic traffic demand and power grid interactions.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104438"},"PeriodicalIF":8.8,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220415","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":"Centralized and decentralized supply chains: Performance maps for comparing the cost-effectiveness of distribution network configurations","authors":"Alessandra Cantini ,&nbsp;Leonardo Leoni ,&nbsp;Saverio Ferraro ,&nbsp;Filippo De Carlo","doi":"10.1016/j.tre.2025.104435","DOIUrl":"10.1016/j.tre.2025.104435","url":null,"abstract":"<div><div>Optimizing Distribution Networks (DNs) is crucial for retailers, impacting service levels and logistics costs. A key DN configuration decision is the stock deployment policy, which entails choosing between centralized, decentralized, and hybrid DNs for each Stock Keeping Unit (SKU). Choosing the stock deployment policy is complex due to many variables influencing the decision (e.g., number of customers served, SKU purchasing costs, customer demand, etc.). Moreover, this decision must be revisited whenever customer demands changes, which can be time-consuming when DN resilience is challenged by geopolitical changes, market trends, and disruptive events. Dimensional Analysis (DA), and particularly the Buckingham Theorem (BT), shows capabilities to support retailers in guiding and streamlining stock deployment decisions. After modeling the stock deployment problem in a mathematical form, BT can identify its influential variables, extract knowledge on how variables mutually interact when affecting the stock deployment performance, and aid informed decision-making on the most cost-effective policy. Accordingly, BT enables creating performance maps which compare the characteristics of different DNs and SKUs, then suggesting similar stock deployment decisions for similar (scaled) DNs and SKUs. Despite the potential utility of these performance maps, no prior study has explored BT’s capabilities for stock deployment decisions. This paper bridges this gap by proposing BT to create supportive maps for multidimensional scaling, similarity analysis, and economic performance prediction across centralized, decentralized, and hybrid DNs. The resultant maps provide retailers with visual decision support tools for associating similar DNs and SKUs with optimal stock deployment policies, ultimately improving DN performance and resilience.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104435"},"PeriodicalIF":8.8,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220351","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":"Multi-period binding freight contract using swing options","authors":"Yuhong Liu,&nbsp;M.I.M. Wahab","doi":"10.1016/j.tre.2025.104419","DOIUrl":"10.1016/j.tre.2025.104419","url":null,"abstract":"<div><div>The truckload freight market is a critical component of the US transportation industry, yet freight contracts used in this market are considered non-binding. Most shippers are challenged with freight rejection problems and forced to source from the spot market. The swing option is an exotic option that allows the holder to purchase or sell a defined quantity of underlying assets. This study proposes the use of swing options as multi-period binding freight contracts between shippers and carriers and builds a fair valuation framework using a mean-reverting process for the freight rates, the Hull-White tree model, and dynamic programming. Numerical examples are given to explain the multi-period price behaviours of the swing option freight contract. Sensitivity analyses are conducted on several key model parameters to understand the impacts of model parameters on the price of the swing option freight contract. Moreover, the performance of six tendering strategies is compared under different market conditions, which helps shippers make informed decisions on purchasing or entering into swing option contracts. Our results show that the shipper in an existing freight contract with a high freight rate benefits the most by tendering to the spot market and purchasing the short-term call swing option freight contract at a low strike price.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104419"},"PeriodicalIF":8.8,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181182","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":"The risk spillover between the crude oil market and the tanker market under the influence of the carbon market","authors":"Bin Meng ,&nbsp;Xinru Zhang ,&nbsp;Jinyang Li ,&nbsp;Liang Lv","doi":"10.1016/j.tre.2025.104445","DOIUrl":"10.1016/j.tre.2025.104445","url":null,"abstract":"<div><div>The low-carbon development of the shipping and crude oil markets is crucial for achieving the EU’s energy and climate goals. Based on the background of the role of the global carbon market, this paper investigates the risk linkage issue between the crude oil and oil tanker markets. Through the Vine-copula-CoVaR model, this paper reveals the cross-market dynamic risk spillover mechanism and measures the risk spillover effects. The results show that: (1) With the extension of the time scale, the impact of carbon market fluctuations on the crude oil and tanker markets is changing, and the degree of long-term risk spillover is greater than that of short-term risk spillover. (2) Carbon market regulation restructures the traditional relationship between the crude oil and tanker markets. (3) Under time–frequency conditions, the CoVaR values of both the tanker and crude oil markets are systematically higher than the VaR values, which means that the risks from the carbon market will amplify the extreme risks of tankers and crude oil systems. (4) The risk spillover relationship during market crisis is stronger than that during stable period. (5) As the time scale extends, the correlation between the carbon market and the oil tanker market gradually increases, and there is a strong intrinsic linkage mechanism between the carbon market and the crude oil market.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"204 ","pages":"Article 104445"},"PeriodicalIF":8.8,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181184","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}