EURO Journal on Transportation and Logistics最新文献

{"title":"Price optimal routing in public transportation","authors":"Ricardo Euler,&nbsp;Niels Lindner,&nbsp;Ralf Borndörfer","doi":"10.1016/j.ejtl.2024.100128","DOIUrl":"https://doi.org/10.1016/j.ejtl.2024.100128","url":null,"abstract":"<div><p>We consider the <em>price-optimal earliest arrival problem</em> in public transit (POEAP) in which we aim to calculate the Pareto-set of journeys with respect to ticket price and arrival time in a public transportation network. Public transit fare structures are often a combination of various fare strategies such as, e.g., distance-based fares, zone-based fares or flat fares. The rules that determine the actual ticket price are often very complex. Accordingly, fare structures are notoriously difficult to model, as it is in general not sufficient to simply assign costs to arcs in a routing graph. Research into POEAP is scarce and usually either relies on heuristics or only considers restrictive fare models that are too limited to cover the full scope of most real-world applications. We therefore introduce <em>conditional fare networks</em> (CFNs), the first framework for representing a large number of real-world fare structures. We show that by relaxing label domination criteria, CFNs can be used as a building block in label-setting multi-objective shortest path algorithms. By the nature of their extensive modeling capabilities, optimizing over CFNs is NP-hard. However, we demonstrate that adapting the multi-criteria RAPTOR (McRAP) algorithm for CFNs yields an algorithm capable of solving POEAP to optimality in less than 400 ms on average on a real-world dataset. By restricting the size of the Pareto-set, running times are further reduced to below 10 ms.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000037/pdfft?md5=08dea96f25a74fd4b5d9a072b3170c46&pid=1-s2.0-S2192437624000037-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139743773","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":"Optimization of bike-sharing repositioning operations: A reactive real-time approach","authors":"","doi":"10.1016/j.ejtl.2024.100138","DOIUrl":"10.1016/j.ejtl.2024.100138","url":null,"abstract":"<div><p>One of the critical issues in the operation of vehicle-sharing systems is the optimization of the fleet repositioning movements. Repositioning implies the artificial movement of vehicles from places where they accumulate to others in which they are scarce. This yields a higher vehicle availability, without over dimensioning the vehicle fleet and while increasing the vehicle utilization rates. In the particular case of bike-sharing systems, repositioning implies to deploy a fleet of small trucks or vans able to move groups of bicycles from one location to another, with the purpose of maximizing the users’ level of service while minimizing the operating agency costs. This repositioning optimization problem has been previously addressed in the operations research field through Mixed Integer Programing (MIP) and its variants, generally facing two limitations. First, its high computational cost, which prevents achieving direct solutions in realistically large systems. So, it has been necessary to develop heuristics and approximations. And second, its reliance and sensitivity to demand forecasts, with its inherent level of uncertainty. Aiming to overcome these weaknesses, this paper presents a strategy based on a real-time pairwise assignment between repositioning trucks and tasks, in order to optimize the bike-sharing repositioning operations. The proposed method is conceptually simple, less dependent on demand predictions, easily implementable in any coding language and applicable to large systems at a low computational cost. These properties make the method appealing to address the repositioning task assignment in any vehicle-sharing system. On a simulated case study, based on <em>Bicing,</em> the bicycle-sharing system in Barcelona, the proposed strategy has been implemented and compared to the MIP-based routing approach. Results show that the proposed real-time pairwise assignment method is able to significantly improve the performance of the repositioning operations, especially in scenarios where the demand forecast is not accurate. Being based on real-time information, the proposed strategy is flexible enough to solve unpredictable situations. So, the proposed strategy can be implemented as an alternative to MIP-based solutions, or as a complementary strategy for dynamic real-time adaptation of static long-term solutions.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S219243762400013X/pdfft?md5=3ad1ea7433351575202703da8c7b9a44&pid=1-s2.0-S219243762400013X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141711860","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 two-stage stochastic programming model for bike-sharing systems with rebalancing","authors":"","doi":"10.1016/j.ejtl.2024.100140","DOIUrl":"10.1016/j.ejtl.2024.100140","url":null,"abstract":"<div><p>We study the problem of determining the target inventory level of stations in a bike-sharing system, when bikes can be rebalanced later during the day. We propose a two-stage stochastic programming formulation, where the target inventory decisions are made at the first stage, while the recourse decisions, related to rebalancing, are made at the second stage. In the literature, the problem of determining the target inventory levels is solved without taking into account the rebalancing problem, or these two problems are solved sequentially. We prove that more efficient bike-sharing systems can be obtained by integrating these two problems. Moreover, we show that our methodology provides better results than the deterministic formulation, and consider an effective matheuristic, based on the solution of the deterministic problem, to solve the stochastic program. Finally, we compare the solutions obtained by our approach with the actual allocation of bikes in the real bike-sharing system of the city of San Francisco. The results show the effectiveness of our approach also in a realistic setting.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000153/pdfft?md5=2d853fa47dc629567d272625e907f0ca&pid=1-s2.0-S2192437624000153-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141848648","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":null,"pages":null},"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":"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":null,"pages":null},"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":"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":"","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":null,"pages":null},"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":null,"pages":null},"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}