EURO Journal on Transportation and Logistics最新文献

{"title":"Inbound traffic capture link-design problem independent of assumptions on users’ route choices","authors":"Ruri Sase,&nbsp;Satoshi Sugiura","doi":"10.1016/j.ejtl.2024.100129","DOIUrl":"10.1016/j.ejtl.2024.100129","url":null,"abstract":"<div><p>In some traffic management situations, a cordon (a set of points at which traffic flows into a given area) is set in a road network to establish a reference for the location of equipment to implement traffic measurements and controls (e.g., traffic volume surveys and congestion charging). However, few studies have focused on the optimum location of a cordon. We devise a problem denoted the inbound traffic capture link-design problem to select the optimum combination of links for inclusion in a cordon. We regard this combination as the minimum number of links that can capture traffic on all routes, under the condition that there is a path between nodes inside the cordon that is not captured. We formulate this model by employing the graph theory concept of the minimum cut, and use the concept of a Steiner tree with auxiliary network flows to express the constraint of ensuring that there is an uncaptured path inside a cordon. After a basic formulation, to obtain an identical cordon, we devise two subsidiary schemes. In addition, we perform a linear relaxation of our method to reduce its computational cost. The results of computational experiments confirm that our model selects the optimal cordon location formed by a combination of capturing links and also outputs an identical cordon as a boundary line of an area. As the model is computationally feasible, even when applied on a large network, we believe it will have a wide range of practical applications.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100129"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000049/pdfft?md5=866665da189a823971e4352d9086ca33&pid=1-s2.0-S2192437624000049-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139815567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of multi-optional pickup time offers in ride-sharing systems","authors":"Jarmo Haferkamp","doi":"10.1016/j.ejtl.2024.100134","DOIUrl":"10.1016/j.ejtl.2024.100134","url":null,"abstract":"<div><p>Ride-sharing systems strive to provide affordable on-demand mobility in urban areas by effectively consolidating incoming transportation requests. To ensure that transportation offers meet travelers’ individual time requirements and constraints, service operators offer multiple pickup times from which travelers can choose. Designing such pickup time offers is challenging due to the uncertainty of both the requirements of the requesting traveler and the efficient fulfillment of future demand. We propose a parametric cost function approximation to balance between maximizing the probability that a traveler will choose an offered pickup time and minimizing the expected vehicle routing effort. We demonstrate the effectiveness of the proposed approach in a comprehensive computational study and provide managerial insights, particularly with respect to the value of information on traveler pickup time requirements.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100134"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000098/pdfft?md5=c22117fc6d0dde9006e4071384ba8cc9&pid=1-s2.0-S2192437624000098-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141132442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A fair multi-commodity two-echelon distribution problem","authors":"Shohre Zehtabian","doi":"10.1016/j.ejtl.2024.100126","DOIUrl":"10.1016/j.ejtl.2024.100126","url":null,"abstract":"<div><p>In the context of a short and local supply chain of fresh produce in the public sector, we introduce a fair multi-commodity two-echelon distribution problem. A decision maker has to decide on the planning of the first-echelon collection trips of commodities from suppliers to distribution centers equitably and on the second-echelon delivery routes of commodities from the centers to customers. In addition to the classic objective of minimizing the total transportation cost in vehicle routing problems, the goal is to make sure that all suppliers receive an equitable service with regard to their profits. This is done by introducing fairness measures into the problem as a set of constraints. We use two widely used inequality metrics from the literature and present a novel problem-specific equity measure as well. We model the problem as a mixed-integer program using an arc-route-based formulation and suggest a matheuristic to solve the problem. Through numerical experiments, we analyze the performance of our matheuristic on a series of generated instances and on the instances of a French fresh produce supply chain from the literature. We evaluate the efficacy of the three used fairness schemes with regard to a series of key performance metrics and investigate the strengths and weaknesses of the different fairness measures. Moreover, we study the trade-off between enforcing fairness and optimizing transportation costs to come up with insights for the managers of the supply chain.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100126"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000013/pdfft?md5=a9c6555203a480f42e62619cee9963c1&pid=1-s2.0-S2192437624000013-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139586655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and solving a corporate vehicle-sharing problem combined with other modes of transport","authors":"Miriam Enzi ,&nbsp;Sophie N. Parragh ,&nbsp;David Pisinger","doi":"10.1016/j.ejtl.2023.100122","DOIUrl":"10.1016/j.ejtl.2023.100122","url":null,"abstract":"<div><p>We consider a car-sharing problem in a company during business hours. The employees, located at one or several offices, have to travel to one or more appointments each with a fixed location and fixed start and end times and return to one of the offices afterwards. Each employee trip can be carried out with one out of several alternative modes of transport. The considered modes of transport are a company car from the company car pool, walking, public transport, bike, and taxi. The aim is to assign modes of transport to employee trips such that the total costs of covering the trips is minimized.</p><p>We first consider that the company is operating a shared fleet of a single type of vehicle and then that the fleet consists of different vehicle types. By relying on minimizing the savings when using a vehicle compared to the cheapest alternative available mode of transport (which is used if no vehicle is assigned to a trip), we do not need to model the alternative modes explicitly. For the case where the vehicle fleet consists of a single type of vehicle, we model the vehicle-sharing problem as a minimum-cost flow problem. Secondly, if multiple types of vehicles are available the problem can be formulated as a multi-commodity flow problem. Since very efficient solution methods are available for these formulations, they are applicable in daily operations.</p><p>We provide a comprehensive computational study for both cases on instances based on demographic, spatial, and economic data of Vienna. We show that our formulations for the problem solve these instances in a few seconds, which makes them usable in an online booking system. In the analysis, we discuss different potential settings. We study different sizes and compositions of the shared fleet, restricted sets of modes of transport, and variations of the objective function.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100122"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437623000195/pdfft?md5=f124a5d29dbeed0c2acca802f4409ee7&pid=1-s2.0-S2192437623000195-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138820610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Order dispatching and vacant vehicles rebalancing for the first-mile ride-sharing problem","authors":"Jinwen Ye ,&nbsp;Giovanni Pantuso ,&nbsp;David Pisinger","doi":"10.1016/j.ejtl.2024.100132","DOIUrl":"https://doi.org/10.1016/j.ejtl.2024.100132","url":null,"abstract":"<div><p>Given a set of transport requests to a transit station and a set of homogeneous vehicle, both geographically dispersed in a business area, the First-Mile Ride-Sharing Problem (FMRSP) consists of finding least cost vehicle routes to transport passengers to the station by shared rides. In this paper we formulate the problem as a mathematical optimization problem and study the effectiveness of preventive movements of idle vehicles (i.e., rebalancing) in order to anticipate future demand. That is, we identify promising rebalancing locations based on historical data and give the model incentives to assign vehicles to such location. We then assess the effectiveness of such movements by simulating online usage of the mathematical model in a rolling-horizon framework. The results show that rebalancing is consistently preferable both in terms of profits and service rate. Particularly, in operating contexts where the station is not centrally located, rebalancing movements increase both profits and service rates by around 30% on average.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100132"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000074/pdfft?md5=84b2bce229720e0fb4da883612f9e352&pid=1-s2.0-S2192437624000074-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140342136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Branch-Price-and-Cut algorithm for the Multi-Commodity two-echelon Distribution Problem","authors":"Matteo Petris ,&nbsp;Claudia Archetti ,&nbsp;Diego Cattaruzza ,&nbsp;Maxime Ogier ,&nbsp;Frédéric Semet","doi":"10.1016/j.ejtl.2024.100139","DOIUrl":"10.1016/j.ejtl.2024.100139","url":null,"abstract":"<div><p>In the Multi-Commodity two-echelon Distribution Problem (MC2DP), multiple commodities are distributed in a two-echelon distribution system involving suppliers, distribution centres and customers. Each supplier may provide different commodities and each customer may request several commodities as well. In the first echelon, capacitated vehicles perform direct trips to transport the commodities from the suppliers to the distribution centres for consolidation purposes. In the second echelon, each distribution centre owns a fleet of capacitated vehicles to deliver the commodities to the customers through multi-stop routes. Commodities are compatible, i.e., they can be mixed in the vehicles. Finally, customer requests can be split by commodities, that is, a customer can be visited by several vehicles, but the total amount of each commodity has to be delivered by a single vehicle. The aim of the MC2DP is to minimize the total transportation cost to satisfy customer demands.</p><p>We propose a set covering formulation for the MC2DP where the exponential number of variables relates to the routes in the delivery echelon. We develop a Branch-Price-and-Cut algorithm (BPC) to solve the problem. The pricing problem results in solving an Elementary Shortest Path Problem with Resource Constraints (ESPPRC) per distribution centre. We tackle the ESPPRC with a label setting dynamic programming algorithm which incorporates ng-path relaxation and a bidirectional labelling search. Pricing heuristics are invoked to speed up the procedure. In addition, the formulation is strengthened by integrating capacity cuts and two families of valid inequalities specific for the multiple commodities aspect of the problem.</p><p>Our approach solves to optimality 439 over the 736 benchmark instances from the literature. The optimality gap of the unsolved instances is 2.1%, on average.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100139"},"PeriodicalIF":2.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000141/pdfft?md5=a549f8cf110df0333404a8737b9ec875&pid=1-s2.0-S2192437624000141-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141692635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The two-flight low risk helicopter transportation problem under the split pickup scenario","authors":"Hans Kellerer ,&nbsp;Vitaly A. Strusevich","doi":"10.1016/j.ejtl.2023.100115","DOIUrl":"10.1016/j.ejtl.2023.100115","url":null,"abstract":"<div><p>The paper considers a special class of routing problems with the objective of minimizing the passengers risk. A major area of application of the low risk models is helicopter transportation widely used in the petroleum industry. In general, the total risk is considered to be proportional to the number of passengers exposed to landings and takeoffs during several multi-leg flights. We give a review of most of the studied models and demonstrate their links with the known problems of combinatorial optimization, such as the minimum latency problem, the multiple deliverymen problem, single machine and parallel machine scheduling, etc. In this paper, we focus on the problem of minimizing total risk, provided that the pickup from a number of locations is performed by two flights, and it is allowed that a location is visited by both flights, splitting the pickup demand. We show that the problem in NP-hard and admits a pseudopolynomial-time dynamic programming algorithm. We also develop a fully polynomial-time approximation scheme and a fast 5/4-approximation algorithm. The results of computational experiments with our algorithms are reported.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100115"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42855938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of principles and methods to decompose large-scale railway scheduling problems","authors":"Florin Leutwiler,&nbsp;Francesco Corman","doi":"10.1016/j.ejtl.2023.100107","DOIUrl":"10.1016/j.ejtl.2023.100107","url":null,"abstract":"<div><p>Providing punctual, reliable and performant services to customers is one main goal of railway network operators. The railway scheduling problem is to determine, ahead of time (timetabling), a plan describing the timing of the operations in a railway network, or updating such plan during operations (rescheduling). By optimization and automation, it is possible to operate more trains on the network, closer to the infrastructure capacity. Especially when the scale and complexity of the scheduling problem is increasing, for large-scale networks and multiple interconnected problems, this is of great value for network operators. When planning or adjusting railway operations becomes increasingly complex, modern scheduling algorithms can bring significant performance and economic benefits. In this survey we review approaches in the state of the art for the problems of railway scheduling. We show how the many different approaches of decomposition proposed in the literature of railway scheduling can be categorized into two general principles. We study different solution methods and identify a list of open topics for dealing with large-scale problems for future research.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100107"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43293917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing inventory control through a data-driven and model-independent framework","authors":"Evangelos Theodorou,&nbsp;Evangelos Spiliotis,&nbsp;Vassilios Assimakopoulos","doi":"10.1016/j.ejtl.2022.100103","DOIUrl":"10.1016/j.ejtl.2022.100103","url":null,"abstract":"<div><p>Machine learning has shown great potential in various domains, but its appearance in inventory control optimization settings remains rather limited. We propose a novel inventory cost minimization framework that exploits advanced decision-tree based models to approximate inventory performance at an item level, considering demand patterns and key replenishment policy parameters as input. The suggested approach enables data-driven approximations that are faster to perform compared to standard inventory simulations, while being flexible in terms of the methods used for forecasting demand or estimating inventory level, lost sales, and number of orders, among others. Moreover, such approximations can be based on knowledge extracted from different sets of items than the ones being optimized, thus providing more accurate proposals in cases where historical data are scarce or highly affected by stock-outs. The framework was evaluated using part of the M5 competition’s data. Our results suggest that the proposed framework, and especially its transfer learning variant, can result in significant improvements, both in terms of total inventory cost and realized service level.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100103"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49230966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep reinforcement learning for stochastic last-mile delivery with crowdshipping","authors":"Marco Silva ,&nbsp;João Pedro Pedroso ,&nbsp;Ana Viana","doi":"10.1016/j.ejtl.2023.100105","DOIUrl":"10.1016/j.ejtl.2023.100105","url":null,"abstract":"<div><p>We study a setting in which a company not only has a fleet of capacitated vehicles and drivers available to make deliveries but may also use the services of occasional drivers (ODs) willing to make deliveries using their own vehicles in return for a small fee. Under such a business model, a.k.a crowdshipping, the company seeks to make all the deliveries at the minimum total cost, i.e., the cost associated with their vehicles plus the compensation paid to the ODs.</p><p>We consider a stochastic and dynamic last-mile delivery environment in which customer delivery orders, as well as ODs available for deliveries, arrive randomly throughout the day, within fixed time windows.</p><p>We present a novel deep reinforcement learning (DRL) approach to the problem that can deal with large problem instances. We formulate the action selection problem as a mixed-integer optimization program.</p><p>The DRL approach is compared against other optimization under uncertainty approaches, namely, sample-average approximation (SAA) and distributionally robust optimization (DRO). The results show the effectiveness of the DRL approach by examining out-of-sample performance.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100105"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43530586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}