EURO Journal on Transportation and Logistics最新文献

{"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}

{"title":"The aircraft recovery problem: A systematic literature review","authors":"Mateus Santana,&nbsp;Jonathan De La Vega,&nbsp;Reinaldo Morabito,&nbsp;Vitória Pureza","doi":"10.1016/j.ejtl.2023.100117","DOIUrl":"10.1016/j.ejtl.2023.100117","url":null,"abstract":"<div><p>Events that cause disruptions to air company flight schedules transporting passengers and cargo are commonplace in practice, and their operational and financial consequences are often relevant. The aircraft recovery problem (ARP) consists of recovering the flight schedules lost due to such events, determining new flight departure times and possible flight cancellations, as well as revising routes for different aircraft. In this study, the main characteristics considered in ARP papers to make the problem as realistic as possible are identified and a systematic literature review is carried out based on seminal studies of the problem in the 1980s. The literature papers are reviewed in terms of the ARP variants studied, the objectives chosen to be optimized and the practical constraints most often considered in real applications, as well as the networks and mathematical formulations to represent the problem and the solution approaches used to deal with it. The aim is to present an up-to-date review of the state-of-the-art of the ARP and to identify possible literature gaps and interesting opportunities for future research on this problem. It is noteworthy that, compared to the simplicity of the first ARP studies, the studies of the following decades tended to involve more complex variants of the problem as a way to become more adherent to current practical environments, requiring more elaborate formulations and solution methods to be properly addressed.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100117"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49258580","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":"Evaluating pricing strategies for premium delivery time windows","authors":"Charlotte Köhler ,&nbsp;Jan Fabian Ehmke ,&nbsp;Ann Melissa Campbell ,&nbsp;Catherine Cleophas","doi":"10.1016/j.ejtl.2023.100108","DOIUrl":"10.1016/j.ejtl.2023.100108","url":null,"abstract":"<div><p>In the challenging environment of attended home deliveries, pricing delivery options can play a crucial role to ensure profitability and service quality of retailers. To differentiate between standard and premium delivery options, many retailers include time windows of various lengths and fees within their offer sets. Even though customers prefer short delivery time windows, longer time windows can help maintaining flexibility and profitability for the retailer. We classify pricing strategies along two dimensions: static versus dynamic price setting and whether an offer set can include one or multiple price points. For static pricing, we implement price configurations that reflect current business practice. For the dynamic pricing, we adapt routing mechanisms that consider the flexibility within the underlying route plan during the booking process and set delivery fees accordingly. To evaluate the pricing strategies under plausibly realistic conditions, we model customer behavior through a nested logit model. This model represents customer choice as sequential decisions between premium and standard time windows. We perform a computational study considering realistic travel and demand data to investigate the effectiveness of static and dynamic time window pricing. Finally, we offer managerial insights and an outlook into applying strategic analysis to decide on price setting strategies.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100108"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43515932","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":"Exact and heuristic approaches to Truck–Drone Delivery Problems","authors":"Júlia C. Freitas,&nbsp;Puca Huachi V. Penna,&nbsp;Túlio A.M. Toffolo","doi":"10.1016/j.ejtl.2022.100094","DOIUrl":"10.1016/j.ejtl.2022.100094","url":null,"abstract":"<div><p>Collaborative delivery employing drones in last-mile delivery has been an extensively studied topic in recent years. In this paper, it is studied Truck–Drone Delivery Problems (TDDPs) in which a traditional delivery truck is gathered with a drone to cut delivery times and costs. The vehicles work together in a hybrid operation involving one drone launching from a larger vehicle that operates as a mobile depot and a recharging platform. The drone launches from the truck with a single package to deliver to a customer. Each drone must return to the truck to recharge batteries, pick up another package, and launch again to a new customer location. This work proposes a novel Mixed Integer Programming (MIP) formulation and a heuristic approach to address the problem. The proposed MIP formulation yields better linear relaxation bounds than previously proposed formulations for all instances, and was capable of optimally solving several unsolved instances from the literature. A hybrid heuristic based on the General Variable Neighborhood Search metaheuristic combining Tabu Search concepts is employed to obtain high-quality solutions for large-size instances. The efficiency of the algorithm was evaluated on 1415 benchmark instances from the literature, and over 80% of the best known solutions were improved.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100094"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48491025","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":"Centralized and decentralized algorithms for two-to-one matching problem in ridehailing systems","authors":"Seyed Mehdi Meshkani,&nbsp;Bilal Farooq","doi":"10.1016/j.ejtl.2023.100106","DOIUrl":"https://doi.org/10.1016/j.ejtl.2023.100106","url":null,"abstract":"<div><p>In the context of on-demand ridehailing, we propose a heuristic matching algorithm where a passenger can share their ride with one more passenger while experiencing a high-quality service with a minimal increase in travel time. To evaluate the performance, we implemented the algorithm in a traffic microsimulator and compared it with a ride-matching algorithm developed by Simonetto et al. (2019) at IBM. Moreover, to enhance efficiency and reduce computational time, we proposed a decentralized version that is based on vehicle-to-infrastructure (V2I) and infrastructure-to-infrastructure (I2I) communication. Application on the downtown Toronto road network demonstrated that the service rate in the centralized version improved by 24%, compared to the IBM algorithm. The decentralized version demonstrated a 25.53 times speedup and the service rate improved by 19%, compared to the IBM algorithm. Furthermore, a sensitivity analysis was conducted over both centralized and decentralized versions to address how different variables and parameters can affect the system’s performance.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100106"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49754221","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":"Aircraft maintenance facility location planning","authors":"Helman I. Stern ,&nbsp;Robert M. Saltzman","doi":"10.1016/j.ejtl.2023.100116","DOIUrl":"10.1016/j.ejtl.2023.100116","url":null,"abstract":"<div><p>This investigation combines the aircraft maintenance routing problem (AMRP) with the aircraft maintenance facility location problem as they are interdependent. Unlike the classical fixed charge location model, aircraft maintenance facility location is not based on static customer demands but on how aircraft move around the airline network while undergoing periodic maintenance checks. Two important factors relevant to this analysis are: (a) aircraft overnight stays at maintenance facilities and airports away from their home bases and (b) the location and cost of maintenance facility construction. There are two possible scenarios concerning the status of maintenance facilities. The first is a tabula rasa case – for a start-up airline with no existing maintenance facilities (AMFLP). The second is an operating airline case with prepositioned maintenance facilities, which we denote as a maintenance facility location update problem (AMFUP). We formulate both as binary integer multicommodity flow problems whose aim is to find the cost-minimizing number, size, and location of the maintenance facilities. Experiments with flight schedules from two regional airlines indicate that total annualized costs are convex in the number of maintenance airports. Though new facility costs tend to dominate, costs associated with noncyclic routes become increasingly important as the number of maintenance airports decreases. Key contributions of this paper are that it (a) demonstrates the superiority of the integration of the aircraft maintenance routing and aircraft maintenance facility location problems, (b) provides a formulation and solution methodology dealing with this significant but under-researched problem, and (c) presents extensive computational experiments, cost and sensitivity analyses for two real life aircraft flight schedules.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100116"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48551181","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 novel repositioning approach and analysis for dynamic ride-hailing problems","authors":"Christian Ackermann,&nbsp;Julia Rieck","doi":"10.1016/j.ejtl.2023.100109","DOIUrl":"https://doi.org/10.1016/j.ejtl.2023.100109","url":null,"abstract":"<div><p>Mobility-on-demand services continue to grow in popularity and could provide a cheap and resource-saving alternative to private vehicles. However, to be truly attractive to the general public, these services must be thoroughly optimized. In this paper, we consider a ride-hailing problem where available vehicles have to be assigned to dynamically arising customer requests and, furthermore, vacant vehicles have to be repositioned to other parts of the service area to balance supply and demand. We propose a novel repositioning strategy based on dynamically created, overlapping zones that addresses identified weaknesses of previous repositioning approaches. While most other ride-hailing studies only consider one specific setting for which a suitable ride-hailing strategy is developed, we further analyze which design decisions in the context of assignment and repositioning work best under different given problem characteristics. Our results show that the proposed repositioning approach outperforms the benchmark approaches in most of the relevant settings, independent of the underlying objective function. Additionally, we show that, especially for low-utilized fleets, the simple nearest-vehicle assignment strategy outperforms matching-based assignment approaches in many settings. The insights gained are analyzed and thoroughly discussed.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100109"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49766345","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":"Pickup and delivery problem with hard time windows considering stochastic and time-dependent travel times","authors":"Zheyu Wang ,&nbsp;Maged Dessouky ,&nbsp;Tom Van Woensel ,&nbsp;Petros Ioannou","doi":"10.1016/j.ejtl.2022.100099","DOIUrl":"10.1016/j.ejtl.2022.100099","url":null,"abstract":"<div><p>Due to the uncertain nature of the traffic system, it is not trivial for delivery companies to reliably satisfy customers’ time windows. To guarantee the reliability of the pickup and delivery service under stochastic and time-dependent travel times, we consider a pickup and delivery problem with hard time windows considering stochastic and time-dependent travel times. We propose a chance-constrained model where the operational cost and the service’s reliability are considered. To quantify the service reliability, every node is associated with a desired node service level, and there exists a global service level, both measured by success probabilities. We present an estimation method for arrival times and success probabilities under stochastic travel and service times. We propose an exact solution approach based on a branch-price-and-cut framework, where a labeling algorithm generates columns. Computational experiments are conducted to assess the effectiveness of the solution framework, and Monte Carlo simulations are used to show that the proposed method can generate routes that satisfy both node and global service levels.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100099"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41922019","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":"The benefit of complete trip information in free-floating carsharing systems","authors":"Claudia Archetti ,&nbsp;Maurizio Bruglieri ,&nbsp;Gianfranco Guastaroba ,&nbsp;M. Grazia Speranza","doi":"10.1016/j.ejtl.2023.100110","DOIUrl":"https://doi.org/10.1016/j.ejtl.2023.100110","url":null,"abstract":"<div><p>Free-floating and instant-access carsharing systems are two features of the most flexible carsharing systems. In the former, users are allowed to freely park the car in any legal parking spot within the boundaries defined by the service operator. In the latter, users are not requested to make any reservation in advance before picking up the car. This paper aims at evaluating the importance of complete trip information in free-floating instant-access carsharing systems. To this aim, we consider a system, referred to as the look-ahead system, where users can reserve a car in advance and are also allowed to directly pick up a car without any reservation. In both cases, the user is requested to specify complete trip details, including the estimated usage duration and the location where the car will be returned. Taking advantage of a complete knowledge of the trip details, the service operator can assign a reservation request to a car that is in use at the time of reservation, provided it will become available at the time and location the user will need it. In its nature, the operational setting we consider is dynamic, as trip information is revealed to the service operator at the time the user requests a car. We also investigate the possibility of suggesting to the user that makes a reservation a pickup location different from the desired one, provided it is not too distant from the latter. We compare the performance of the look-ahead system with the case no information is anticipated, which resembles the service provided by the main carsharing operators currently active in Milan (Italy). Additionally, we use, as a benchmark, the static case where all the information about the users requests (pickup and return locations, as well as delivery time) is known before the start of the planning horizon. We consider a system with no car relocations performed by ad-hoc operators. This enables us to measure the pure benefit of anticipated information, i.e., the benefit coming only from knowing in advance where and when the vehicles will be returned, purged from potential vehicles availability related to relocation operations. The matching between user requests and cars is obtained, for the look-ahead system, iteratively at fixed time intervals through the solution of a Binary Linear Program (BLP) and, for the benchmark case, through the solution of a single BLP. No optimization model is needed for the case where no information is anticipated. A simulation study, based on real-world data from the city of Milan, shows that the look-ahead system can satisfy a number of requests much greater than the case without anticipated information and close to the benchmark case. Moreover, we perform a sensitivity analysis on different parameters, including the maximum distance a user is available to walk and the minimum amount of anticipation requested to users for booking requests, showing their impact on the performance of the systems.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100110"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49766320","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":"Solving the Traveling Salesman Problem with release dates via branch and cut","authors":"Agustín Montero ,&nbsp;Isabel Méndez-Díaz ,&nbsp;Juan José Miranda-Bront","doi":"10.1016/j.ejtl.2023.100121","DOIUrl":"https://doi.org/10.1016/j.ejtl.2023.100121","url":null,"abstract":"<div><p>In this paper we study the Traveling Salesman Problem with release dates (TSP-rd) and completion time minimization. The TSP-rd considers a single vehicle and a set of customers that must be served exactly once with goods that arrive to the depot over time, during the planning horizon. The time at which each requested good arrives is called <em>release date</em> and it is known in advance. The vehicle can perform multiple routes, however, it cannot depart to serve a customer before the associated release date. Thus, the release date of the customers in each route must not be greater than the starting time of the route. The objective is to determine a set of routes for the vehicle, starting and ending at the depot, where the completion time needed to serve all customers is minimized. We propose a new Integer Linear Programming model and develop a branch and cut algorithm with tailored enhancements to improve its performance. The algorithm proved to be able to significantly reduce the computation times when compared to a compact formulation tackled using a commercial mathematical programming solver, obtaining 24 new optimal solutions on benchmark instances with up to 30 customers within one hour. We further extend the benchmark to instances with up to 50 customers where the algorithm proved to be efficient. Building upon these results, the proposed model is adapted to new TSP-rd variants (Capacitated and Prize-Collecting TSP), with different objectives: completion time minimization and traveling distance minimization. To the best of our knowledge, our work is the first in-depth study to report extensive results for the TSP-rd through a branch and cut, establishing a baseline and providing insights for future approaches. Overall, the approach proved to be very effective and gives a flexible framework for several variants, opening the discussion about formulations, algorithms and new benchmark instances.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"12 ","pages":"Article 100121"},"PeriodicalIF":2.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437623000183/pdfft?md5=94c46b35a7aa04ddfe0a25abf9715b0f&pid=1-s2.0-S2192437623000183-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138471862","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}