Baptiste Coutton , Dario Pacino , Klaus Holst , Stefan Guericke , Martin Philip Kidd
{"title":"Heuristic approaches for freight containerization with business rules","authors":"Baptiste Coutton , Dario Pacino , Klaus Holst , Stefan Guericke , Martin Philip Kidd","doi":"10.1016/j.tre.2025.104063","DOIUrl":"10.1016/j.tre.2025.104063","url":null,"abstract":"<div><div>Manufacturing companies who ship goods globally often rely on external Logistics Service Providers (LSPs) to manage the containerization and transportation of their freight. Those LSPs are usually required to follow rules when deciding how to mix the goods in the containers, which complicates the planning task. In this paper, we study such a freight containerization problem with a specific type of cargo mixing requirements recurrently faced by an international LSP. We show that this problem can be formulated as a Multi-Class Constrained Variable Size Bin Packing Problem: given a set of items that all have a size and a fixed number of classes for which they can take certain values, the objective is to pack the items in a minimum-cost set of bins while ensuring that the size capacity and maximum number of distinct values per class are not exceeded in any of the bins. We propose two adapted and one novel greedy heuristics, as well as an Adaptive Large Neighborhood Search (ALNS) metaheuristic, to find feasible solutions to the problem. We also provide a pattern-based formulation that is used to obtain lower bounds using a Column Generation approach. Using three extensive datasets, including a novel one with up to 1000 items and 5 classes reflecting real industrial cases, we show that the novel greedy heuristic outperforms the adaptations of the existing ones and that our ALNS yields significantly better solutions than a commercial solver within a mandatory 5-minute time limit. Practical insights are given about the solutions for the industrial benchmark.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104063"},"PeriodicalIF":8.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704690","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":"Preemptive facility interdiction under damage uncertainty","authors":"Mahdi Noorizadegan , Abbas Seifi , Hossein Esmaeeli , Reza Zanjirani Farahani","doi":"10.1016/j.tre.2025.104081","DOIUrl":"10.1016/j.tre.2025.104081","url":null,"abstract":"<div><div>The preemptive facility interdiction problem aims to disable or diminish future threats from adversaries by proactively targeting their critical facilities. This research generalizes a preemptive facility interdiction problem with capacitated facilities. The problem is formulated as a bi-level optimization problem in which the interdictor, at the upper level, decides to attack several facilities to maximize the supply cost of the adversary (defender) force at the lower level. We make a realistic assumption that the magnitude of damage after the attack decisions is uncertain, leading to the partially available capacity for the defender to supply some of the demand points. The network defender may allow for a demand shortage while having the option to reallocate some of the demands to alternative facilities at a fixed cost and potentially higher transportation costs. The defender reacts to the attack to keep the supply network operational at the minimum expected cost.</div><div>This problem is NP-hard and computationally intensive to solve, particularly on a large scale. We have designed a cutting plane incorporating (1) optimality cuts to guide us towards an optimal solution and (2) so-called minus-k cuts devised based on the dominant solutions to improve efficiency. We have conducted extensive experiments on our facility interdiction problem to address the practical aspects of the problem by sensitivity analysis and the computational aspects of the solution method by solving relatively large instances with a small optimality gap. Furthermore, we draw some practical insights into how the decision-making process is affected in such an interdiction problem.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104081"},"PeriodicalIF":8.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704691","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}
Nannan He , Sijing Liu , Jason Cao , Guoqi Li , Ming Jian
{"title":"Identifying the critical features influencing warehouse rental prices and their nonlinear associations: A spatial machine learning approach","authors":"Nannan He , Sijing Liu , Jason Cao , Guoqi Li , Ming Jian","doi":"10.1016/j.tre.2025.104092","DOIUrl":"10.1016/j.tre.2025.104092","url":null,"abstract":"<div><div>Warehouses play a crucial role in freight transportation, and their pricing strategies affect warehouse location choices and associated environmental impacts. Although most firms rent storage spaces, limited studies have examined warehouse rental prices (WRP). Furthermore, most studies assume a pre-defined relationship between WRP and its correlates. This study applies spatial machine learning models to warehouse rental data in Shanghai to examine their nonlinear associations. The results show that the primary factors influencing WRP include spatial dependence among warehouses, location and neighborhood attributes, and the floor level of warehouse spaces, whereas lease and service-related factors contribute minimally. Moreover, spatial dependence leads to segmented markets, with high-rent warehouses clustering in the central urban area and around logistics parks and transportation terminals outside the central area. Additionally, most primary correlates exhibit irregular nonlinear relationships with WRP, which shed light on warehouse pricing mechanisms and provide guidance for location choices.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104092"},"PeriodicalIF":8.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697122","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}
Tong Nie , Junlin He , Yuewen Mei , Guoyang Qin , Guilong Li , Jian Sun , Wei Ma
{"title":"Joint estimation and prediction of city-wide delivery demand: A large language model empowered graph-based learning approach","authors":"Tong Nie , Junlin He , Yuewen Mei , Guoyang Qin , Guilong Li , Jian Sun , Wei Ma","doi":"10.1016/j.tre.2025.104075","DOIUrl":"10.1016/j.tre.2025.104075","url":null,"abstract":"<div><div>The proliferation of e-commerce and urbanization has significantly intensified delivery operations in urban areas, boosting the volume and complexity of delivery demand. Data-driven predictive methods, especially those utilizing machine learning techniques, have emerged to handle these complexities in urban delivery demand management problems. One particularly pressing issue that has yet to be sufficiently addressed is the joint estimation and prediction of city-wide delivery demand, as well as the generalization of the model to new cities. To this end, we formulate this problem as a transferable graph-based spatiotemporal learning task. First, an individual-collective message-passing neural network model is formalized to capture the interaction between demand patterns of associated regions. Second, by exploiting recent advances in large language models (LLMs), we extract general geospatial knowledge encodings from the unstructured locational data using the embedding generated by LLMs. Last, to encourage the cross-city generalization of the model, we integrate the encoding into the demand predictor in a transferable way. Comprehensive empirical evaluation results on two real-world delivery datasets, including eight cities in China and the US, demonstrate that our model significantly outperforms state-of-the-art baselines in accuracy, efficiency, and transferability. <strong>PyTorch implementation is available at:</strong> <span><span>https://github.com/tongnie/IMPEL</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104075"},"PeriodicalIF":8.3,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696148","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}
{"title":"Joint matching and pricing for taxi drive-by sensing","authors":"Binzhou Yang , Ke Han , Shenglin Liu , Ruijie Li","doi":"10.1016/j.tre.2025.104071","DOIUrl":"10.1016/j.tre.2025.104071","url":null,"abstract":"<div><div>Drive-by sensing is a promising data collection paradigm that leverages the mobilities of vehicles to survey urban environments at low costs, contributing to the positive externality of urban transport activities. Focusing on e-hailing services, this paper explores the sensing potential of taxi fleets, by designing a joint matching and pricing scheme based on a double auction process. The matching module maximizes the sensing utility by prioritizing trips with high sensing potentials, and the pricing module allocates the corresponding social welfare according to the participants’ contributions to the sensing utility. We show that the proposed scheme is allocative efficient, individually rational, budget balancing, envy-free, and group incentive compatible. The last notion guarantees that the entire group of participants will always end up with the same total utility, regardless of the individual mis-reporting behavior. Extensive numerical tests based on a real-world scenario reveal that the sensing externality can be well aligned with the level of service and budget balance. Various managerial insights regarding the applicability and efficacy of the proposed scheme are generated through scenario-based sensitivity analyses.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104071"},"PeriodicalIF":8.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685541","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}
Baoli Liu , Xincheng Wang , Zehao Wang , Jianfeng Zheng , Dian Sheng
{"title":"Modeling and solving the joint berth allocation and vessel sequencing problem with speed optimization in a busy seaport","authors":"Baoli Liu , Xincheng Wang , Zehao Wang , Jianfeng Zheng , Dian Sheng","doi":"10.1016/j.tre.2025.104089","DOIUrl":"10.1016/j.tre.2025.104089","url":null,"abstract":"<div><div>Vessel sequencing, speed optimization, and berth allocation comprise the primary interventions for servicing calling vessels in a busy seaport. The objectives are to minimize vessel completion time and reduce carbon emissions, thus balancing port service efficiency with environmental sustainability. Despite interdependent, these challenges have often been addressed in isolation, leading to sub-optimal or even infeasible solutions for vessel services. In this paper, we propose a bi-objective mixed-integer linear programming model that jointly optimizes the allocation of vessels to berths, as well as the sequencing and sailing speeds of vessels within the channel. To solve this model, we develop a tailored non-dominated sorting genetic algorithm incorporating reinforcement learning. Several efficient methods are presented to improve the performance of the developed algorithm. We also introduce a new relative distance-based metric to evaluate Pareto solutions. Extensive computational experiments on Jingtang Port, China, show that our algorithm outperforms the benchmark algorithms from the literature, yielding far superior solutions in shorter computational times. Various Pareto solutions are provided, based on which trade-offs between service efficiency and environmental sustainability are analyzed and some managerial insights are outlined.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104089"},"PeriodicalIF":8.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685540","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":"Parcel delivery by vehicle and drone in ordered customer neighborhoods","authors":"Ahmed Ghoniem , Semih Boz , Amro M. El-Adle","doi":"10.1016/j.tre.2025.104047","DOIUrl":"10.1016/j.tre.2025.104047","url":null,"abstract":"<div><div>We consider a last-mile parcel delivery problem where a vehicle with a companion drone visits a set of ordered neighborhoods, following a line of travel that starts and ends at the depot. The decision-maker restricts the drone to fly within the neighborhood being serviced by the vehicle and seeks to optimize the vehicle and drone operations so that the total time to return to the depot, upon completing all deliveries, is minimized. The problem is formulated as a mixed-integer program, which is enhanced via cut-set constraints and valid inequalities derived using the Reformulation-Linearization Technique (RLT). Further, we investigate the logistical and computational effects of optionally imposing street precedence rules, based on training data from numerous optimized solutions for instances constructed in Amherst, MA (USA). Our study examines the computational tractability of the baseline model, the usefulness of imposing valid inequalities, and the impact of enforcing street precedence rules. Remarkably, enforcing RLT-based valid inequalities enables, in our experience, optimal solutions for instances having up to 200 customers within manageable times, thereby yielding a practical optimization-based framework for decision-makers.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104047"},"PeriodicalIF":8.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685542","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":"Buy-online-pickup-in-store service: A precarious competing strategy","authors":"Lina Zhang , Yumeng Zhang","doi":"10.1016/j.tre.2025.104050","DOIUrl":"10.1016/j.tre.2025.104050","url":null,"abstract":"<div><div>The widespread adoption of buy-online-pickup-in-store (BOPS) services has attracted significant research attention, particularly regarding when an online retailer should deploy BOPS service for last-mile delivery (LMD). This study examines the efficiency of BOPS adoption in a competing environment. Using a game-theoretical model within a duopoly framework, we investigate the pricing and BOPS service design decisions between competing retailers with varying home delivery (HD) service qualities. The results reveal how a retailer responds to its competitor’s different BOPS adoption strategies. When it is not yet available in the market, BOPS service provides a competitive advantage as the only BOPS-offering retailer enjoys increased profits. We identify distinctive profit mechanisms for retailers with a higher or lower level of HD service quality: enhanced competitive differentiation effect for the former and quality perception improvement effect for the latter. Nevertheless, our analysis shows that when both retailers adopt BOPS service, they reach an equilibrium where at least one retailer is worse off. The prisoner’s dilemma may occur where both retailers end up in a suboptimal position, and the likelihood of this dilemma is influenced by their HD service quality differentiation. Ultimately, while seemingly beneficial, BOPS service is a precarious competitive strategy that may trap retailers. Our findings contribute to the expanding BOPS literature and offer valuable practical implications for online retailing.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104050"},"PeriodicalIF":8.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685539","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}
Steffen J.S. Bakker , Jonas Martin , E. Ruben van Beesten , Ingvild Synnøve Brynildsen , Anette Sandvig , Marit Siqveland , Antonia Golab
{"title":"STraM: A strategic network design model for national freight transport decarbonization","authors":"Steffen J.S. Bakker , Jonas Martin , E. Ruben van Beesten , Ingvild Synnøve Brynildsen , Anette Sandvig , Marit Siqveland , Antonia Golab","doi":"10.1016/j.tre.2025.104076","DOIUrl":"10.1016/j.tre.2025.104076","url":null,"abstract":"<div><div>National freight transport models are valuable tools for assessing the impact of various policies and investments on achieving decarbonization targets under different future scenarios. However, these models struggle to address several critical elements necessary for strategic planning, such as the development and adoption of new fuel technologies over time, inertia in transport fleets, and uncertainty surrounding future transport costs. In this paper, we develop a strategic network design model, named STraM, that explicitly incorporates these key factors. STraM, being a two-stage stochastic program, effectively handles long-term uncertainty by considering different future scenarios in its decision-making process.It provides a network design plan that includes infrastructure investments and fuel technology decisions, aiming to achieve cost-effective decarbonization of the freight transport system. The model output can be used as input for higher-resolution national freight transport models to yield results with greater operational detail. We demonstrate the application of STraM through a case study of Norway, offering valuable insights into the strategic planning of decarbonizing freight transport.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"197 ","pages":"Article 104076"},"PeriodicalIF":8.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685538","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}