Pub Date : 2025-01-01DOI: 10.1016/j.ejtl.2025.100153
Fatemeh Mousapour, Rajan Batta, Jose L. Walteros
Police patrolling is a combination of proactive and reactive tasks. The initial focus is on the development and analysis of a deterministic model which has proactive patrolling tasks consisting of hot spot and general patrolling duties. Two different formulations are developed to address the problem: a compact arc-based and an extensive path-based formulation embedded in a column generation procedure. These formulations incorporate three metrics of efficiency and fairness: density, equity, and dispersion. Our model has discrete time steps and seeks to make a balance between hot spot and general patrolling duties by defining details of patrolling routes. The model allows a patrol unit to be at a hot spot for multiple consecutive time steps, thereby allowing foot patrolling to be used at a hot spot. We embed the deterministic model in a simulation environment for the purpose of defining proactive patrolling routes while responding to the calls for service. Numerical experiments are conducted to (a) evaluate the computational efficiency of the proposed methods, and (b) explore sensitivity analysis with respect to key parameters. A crime-data based case study is developed to illustrate the utility of the models and methods in a practical situation.
{"title":"On the development and analysis of a comprehensive police patrolling model","authors":"Fatemeh Mousapour, Rajan Batta, Jose L. Walteros","doi":"10.1016/j.ejtl.2025.100153","DOIUrl":"10.1016/j.ejtl.2025.100153","url":null,"abstract":"<div><div>Police patrolling is a combination of <em>proactive</em> and <em>reactive</em> tasks. The initial focus is on the development and analysis of a deterministic model which has <em>proactive</em> patrolling tasks consisting of <em>hot spot</em> and <em>general</em> patrolling duties. Two different formulations are developed to address the problem: a compact arc-based and an extensive path-based formulation embedded in a column generation procedure. These formulations incorporate three metrics of efficiency and fairness: density, equity, and dispersion. Our model has discrete time steps and seeks to make a balance between <em>hot spot</em> and <em>general</em> patrolling duties by defining details of patrolling routes. The model allows a patrol unit to be at a hot spot for multiple consecutive time steps, thereby allowing foot patrolling to be used at a hot spot. We embed the deterministic model in a simulation environment for the purpose of defining <em>proactive</em> patrolling routes while responding to the calls for service. Numerical experiments are conducted to (a) evaluate the computational efficiency of the proposed methods, and (b) explore sensitivity analysis with respect to key parameters. A crime-data based case study is developed to illustrate the utility of the models and methods in a practical situation.</div></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"14 ","pages":"Article 100153"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143104239","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}
Pub Date : 2025-01-01DOI: 10.1016/j.ejtl.2025.100154
Kamyla Maria Ferreira , Claudia Archetti , Diego Delle Donne , Reinaldo Morabito , Pedro Munari
This paper introduces the Green Commodity constrained Split Delivery Vehicle Routing Problem (GC-SDVRP), which involves designing efficient and environmentally friendly delivery routes that reduce the CO emissions associated with transporting multiple commodities. In this problem, different commodities demanded by a customer can be delivered by one or more vehicles, if beneficial, which poses additional modeling and solution challenges. We propose a relaxed formulation that provides a lower bound on the optimal value of the GC-SDVRP, and adapt two other formulations from the literature to address this problem. Additionally, we develop a branch-and-cut (BC) method based on two of these formulations, and introduce a procedure for deriving feasible solutions to the GC-SDVRP from solutions obtained with the relaxed formulations. The results of computational experiments performed on benchmark instances indicate the superior performance of the BC method based on the proposed formulation. Furthermore, they show that, contrary to the traditional objective of minimizing distance, the GC-SDVRP is significantly easier to solve to optimality and can reduce CO emissions by 2.59% compared to the problem that minimizes total travel distance. Our investigation also reveals that increasing vehicle capacity improves solution quality in the GC-SDVRP, while split delivery can enable further reductions in CO emissions. Finally, although increasing the number of commodities imposes challenges in solving the problem, the possibility of split delivery mitigates its impact on the value of the final solution, indicating that an increase in the number of commodities does not necessarily result in higher CO emissions.
{"title":"The commodity constrained split delivery vehicle routing problem considering carbon emission: Formulations and a branch-and-cut method","authors":"Kamyla Maria Ferreira , Claudia Archetti , Diego Delle Donne , Reinaldo Morabito , Pedro Munari","doi":"10.1016/j.ejtl.2025.100154","DOIUrl":"10.1016/j.ejtl.2025.100154","url":null,"abstract":"<div><div>This paper introduces the Green Commodity constrained Split Delivery Vehicle Routing Problem (GC-SDVRP), which involves designing efficient and environmentally friendly delivery routes that reduce the CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions associated with transporting multiple commodities. In this problem, different commodities demanded by a customer can be delivered by one or more vehicles, if beneficial, which poses additional modeling and solution challenges. We propose a relaxed formulation that provides a lower bound on the optimal value of the GC-SDVRP, and adapt two other formulations from the literature to address this problem. Additionally, we develop a branch-and-cut (BC) method based on two of these formulations, and introduce a procedure for deriving feasible solutions to the GC-SDVRP from solutions obtained with the relaxed formulations. The results of computational experiments performed on benchmark instances indicate the superior performance of the BC method based on the proposed formulation. Furthermore, they show that, contrary to the traditional objective of minimizing distance, the GC-SDVRP is significantly easier to solve to optimality and can reduce CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions by 2.59% compared to the problem that minimizes total travel distance. Our investigation also reveals that increasing vehicle capacity improves solution quality in the GC-SDVRP, while split delivery can enable further reductions in CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions. Finally, although increasing the number of commodities imposes challenges in solving the problem, the possibility of split delivery mitigates its impact on the value of the final solution, indicating that an increase in the number of commodities does not necessarily result in higher CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions.</div></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"14 ","pages":"Article 100154"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488411","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}
Pub Date : 2025-01-01DOI: 10.1016/j.ejtl.2024.100149
Somporn Sahachaiseree , Mohammad Sadrani , Constantinos Antoniou
Mass rapid transit systems around the world are typically designed for all-stop operation schemes, in which train overtaking is not possible. To accelerate transit operation, the conventional A/B skip-stop scheme may be planned. This research explores alternative skip-stop schemes with three stop patterns, aiming to better match transit services with the spatial distribution of travel demand. The proposed generalised skip-stop operation model considers both the total cost of passengers and operator. A genetic algorithm is employed to solve the stop-plan optimisation problem, and a heuristic is tailored to determine an optimal dispatch headway for the respective stop plan. Based on computational experiments using synthetic data, the results suggest that skip-stop schemes have the potential to reduce total time costs by about 10%, particularly when there are structured demand concentrations, transit systems can operate safely with low time headway and short-distance demand is low. Although the total-cost saving of the best A/B skip-stop plan found is generally superior to those of other three-pattern skip-stop schemes, a three-pattern skip-stop scheme was found to offer a better total-cost saving in a scenario without short-distance travel demands. Overall, this research offers valuable insights into the potential benefits and limitations of different skip-stop schemes, contributing to a better understanding of their impact on passengers and operators.
{"title":"Stop plan optimisation for three-pattern skip-stop schemes for urban rail transit systems","authors":"Somporn Sahachaiseree , Mohammad Sadrani , Constantinos Antoniou","doi":"10.1016/j.ejtl.2024.100149","DOIUrl":"10.1016/j.ejtl.2024.100149","url":null,"abstract":"<div><div>Mass rapid transit systems around the world are typically designed for all-stop operation schemes, in which train overtaking is not possible. To accelerate transit operation, the conventional A/B skip-stop scheme may be planned. This research explores alternative skip-stop schemes with three stop patterns, aiming to better match transit services with the spatial distribution of travel demand. The proposed generalised skip-stop operation model considers both the total cost of passengers and operator. A genetic algorithm is employed to solve the stop-plan optimisation problem, and a heuristic is tailored to determine an optimal dispatch headway for the respective stop plan. Based on computational experiments using synthetic data, the results suggest that skip-stop schemes have the potential to reduce total time costs by about 10%, particularly when there are structured demand concentrations, transit systems can operate safely with low time headway and short-distance demand is low. Although the total-cost saving of the best A/B skip-stop plan found is generally superior to those of other three-pattern skip-stop schemes, a three-pattern skip-stop scheme was found to offer a better total-cost saving in a scenario without short-distance travel demands. Overall, this research offers valuable insights into the potential benefits and limitations of different skip-stop schemes, contributing to a better understanding of their impact on passengers and operators.</div></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"14 ","pages":"Article 100149"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103819","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}
Pub Date : 2025-01-01DOI: 10.1016/j.ejtl.2025.100152
Sanchari Guha Niyogi
Electric vehicles (EVs) are central to global efforts to reduce transportation emissions, yet limited charging infrastructure remains a primary barrier to widespread adoption. Governments worldwide have implemented various subsidies for EV purchasers and manufacturers, alongside green tax schemes, to incentivise infrastructure expansion and boost EV uptake. This research explores the efficacy of policy combinations — specifically purchase-based or per-station subsidies and green taxes — in a duopolistic market setting. By employing a game-theoretic model comprising profit-maximising EV and gasoline vehicle (GV) manufacturers, a population of utility-maximising consumers, and a social welfare-maximising government, we observe that a purchase-based subsidy in combination with a green tax provides a win–win–win outcome for the government and the manufacturers. Incorporating consumers’ EV-related anxieties, our analysis suggests that a green tax, either on its own or combined with subsidies, is the most effective policy for governments aiming to maximise social welfare. In markets characterised by diverse and sometimes misinformed consumers, a policy mix of green taxes and charging subsidies proves especially beneficial when the environmental impact of EV adoption is substantial. Additionally, when accounting for network effects, which could result in congested charging stations, pairing consumer subsidies with a green tax emerges as the preferential policy. Manufacturers and policymakers are provided with multifaceted insights that aid in conceptualising electric mobility.
{"title":"Accelerating the electric vehicle revolution: Policy implications of charging subsidies and green taxes","authors":"Sanchari Guha Niyogi","doi":"10.1016/j.ejtl.2025.100152","DOIUrl":"10.1016/j.ejtl.2025.100152","url":null,"abstract":"<div><div>Electric vehicles (EVs) are central to global efforts to reduce transportation emissions, yet limited charging infrastructure remains a primary barrier to widespread adoption. Governments worldwide have implemented various subsidies for EV purchasers and manufacturers, alongside green tax schemes, to incentivise infrastructure expansion and boost EV uptake. This research explores the efficacy of policy combinations — specifically purchase-based or per-station subsidies and green taxes — in a duopolistic market setting. By employing a game-theoretic model comprising profit-maximising EV and gasoline vehicle (GV) manufacturers, a population of utility-maximising consumers, and a social welfare-maximising government, we observe that a purchase-based subsidy in combination with a green tax provides a win–win–win outcome for the government and the manufacturers. Incorporating consumers’ EV-related anxieties, our analysis suggests that a green tax, either on its own or combined with subsidies, is the most effective policy for governments aiming to maximise social welfare. In markets characterised by diverse and sometimes misinformed consumers, a policy mix of green taxes and charging subsidies proves especially beneficial when the environmental impact of EV adoption is substantial. Additionally, when accounting for network effects, which could result in congested charging stations, pairing consumer subsidies with a green tax emerges as the preferential policy. Manufacturers and policymakers are provided with multifaceted insights that aid in conceptualising electric mobility.</div></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"14 ","pages":"Article 100152"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422715","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}
Pub Date : 2025-01-01DOI: 10.1016/j.ejtl.2024.100148
Marielle Christiansen , Kjetil Fagerholt , David Pisinger
This paper gives a detailed overview of the last 50 years of research in maritime transportation, with special focus on operations research techniques applied to the seaside operations. We describe the evolution in industrial, tramp and liner shipping, identify the driving trends, and discuss future challenges.
{"title":"Fifty years on maritime transportation","authors":"Marielle Christiansen , Kjetil Fagerholt , David Pisinger","doi":"10.1016/j.ejtl.2024.100148","DOIUrl":"10.1016/j.ejtl.2024.100148","url":null,"abstract":"<div><div>This paper gives a detailed overview of the last 50 years of research in maritime transportation, with special focus on operations research techniques applied to the seaside operations. We describe the evolution in industrial, tramp and liner shipping, identify the driving trends, and discuss future challenges.</div></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"14 ","pages":"Article 100148"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143104237","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}
Pub Date : 2025-01-01DOI: 10.1016/j.ejtl.2025.100155
Pedro José Correia Duarte , Stéphane Dauzère-Pérès , Dennis Huisman , Carlo Mannino , Giorgio Sartor , Norman Weik , Philipp Widmann
This survey paper discusses the literature on Operations Research (OR) models and algorithms for railway planning in the last decades. Since infrastructure and rolling stock are two resources that are both very capital-intensive and characterize the railway system, we focus on timetabling and rolling stock planning problems. For timetabling, we also classify the literature among two dimensions, namely the decision level (strategic, tactical, operational) and the type of network infrastructure (dependent routes, independent routes). We also discuss robustness aspects in both planning problems.
We focus the discussion of the literature on the applicability of the models in the European context, where different types of trains (high-speed passenger trains, high-frequent suburban trains and freight trains) often share the same tracks and the organization of the railways is usually split between an infrastructure manager and one or more railway undertakings operating the trains.
We conclude the paper with some challenges and future research directions.
{"title":"50 years of OR in railway timetabling and rolling stock planning","authors":"Pedro José Correia Duarte , Stéphane Dauzère-Pérès , Dennis Huisman , Carlo Mannino , Giorgio Sartor , Norman Weik , Philipp Widmann","doi":"10.1016/j.ejtl.2025.100155","DOIUrl":"10.1016/j.ejtl.2025.100155","url":null,"abstract":"<div><div>This survey paper discusses the literature on Operations Research (OR) models and algorithms for railway planning in the last decades. Since infrastructure and rolling stock are two resources that are both very capital-intensive and characterize the railway system, we focus on timetabling and rolling stock planning problems. For timetabling, we also classify the literature among two dimensions, namely the decision level (strategic, tactical, operational) and the type of network infrastructure (dependent routes, independent routes). We also discuss robustness aspects in both planning problems.</div><div>We focus the discussion of the literature on the applicability of the models in the European context, where different types of trains (high-speed passenger trains, high-frequent suburban trains and freight trains) often share the same tracks and the organization of the railways is usually split between an infrastructure manager and one or more railway undertakings operating the trains.</div><div>We conclude the paper with some challenges and future research directions.</div></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"14 ","pages":"Article 100155"},"PeriodicalIF":2.1,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578362","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}
Pub Date : 2024-01-01DOI: 10.1016/j.ejtl.2024.100145
Andreas Bärmann , Alexander Martin , Jonasz Staszek
In this work, we consider the integrated problem of locomotive scheduling and driver assignment in rail freight companies. Our aim is to compute an optimal simultaneous assignment of locomotives and drivers to the trains listed in a given order-book. Mathematically, this leads to the combination of a set-packing problem with compatibility constraints and a multi-commodity-flow problem. We develop a binary-programming formulation to model the given task and improve it by performing a clique-based tightening of the original set-packing inequalities. The objective function of this model makes sure that as many trains as possible are running. To handle the computational complexity of the problem, we introduce a novel decomposition approach which decomposes the problem into a master locomotive scheduling problem and a subproblem for driver assignment. It exploits the fact that the master problem is empirically much easier to solve than the subproblem. For any fixed solution of the master problem, we can use the subproblem to either confirm feasibility of the master solution or to derive valid inequalities from various constraint classes to cut the infeasible master solution off and reiterate. To further improve solution times, we also develop a presolve heuristic. We demonstrate the potential of the presented method by solving a large-scale real-world problem instance provided by our industry partner DB Cargo Polska S.A., as well as a set of derived realistic instances.
在这项工作中，我们考虑的是铁路货运公司机车调度和司机分配的综合问题。我们的目标是计算出机车和司机对给定订单所列列车的最优同步分配。在数学上，这导致了一个带有兼容性约束的集合包装问题和一个多商品流问题的结合。我们开发了一种二元编程模型来模拟给定任务，并通过对原始的集合包装不等式进行基于类群的紧缩来改进该模型。该模型的目标函数确保尽可能多的列车运行。为了解决该问题的计算复杂性，我们引入了一种新颖的分解方法，将该问题分解为主机车调度问题和司机分配子问题。它利用了主问题比子问题更容易解决这一事实。对于主问题的任何固定解，我们都可以利用子问题来确认主问题解的可行性，或者从各种约束类别中推导出有效的不等式，以切断不可行的主问题解，并重新进行求解。为了进一步缩短求解时间，我们还开发了一种预解启发式。我们通过解决我们的行业合作伙伴 DB Cargo Polska S.A. 提供的一个大型实际问题实例以及一组衍生的现实实例，展示了所介绍方法的潜力。
{"title":"A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport","authors":"Andreas Bärmann , Alexander Martin , Jonasz Staszek","doi":"10.1016/j.ejtl.2024.100145","DOIUrl":"10.1016/j.ejtl.2024.100145","url":null,"abstract":"<div><div>In this work, we consider the integrated problem of locomotive scheduling and driver assignment in rail freight companies. Our aim is to compute an optimal simultaneous assignment of locomotives and drivers to the trains listed in a given order-book. Mathematically, this leads to the combination of a set-packing problem with compatibility constraints and a multi-commodity-flow problem. We develop a binary-programming formulation to model the given task and improve it by performing a clique-based tightening of the original set-packing inequalities. The objective function of this model makes sure that as many trains as possible are running. To handle the computational complexity of the problem, we introduce a novel decomposition approach which decomposes the problem into a master locomotive scheduling problem and a subproblem for driver assignment. It exploits the fact that the master problem is empirically much easier to solve than the subproblem. For any fixed solution of the master problem, we can use the subproblem to either confirm feasibility of the master solution or to derive valid inequalities from various constraint classes to cut the infeasible master solution off and reiterate. To further improve solution times, we also develop a presolve heuristic. We demonstrate the potential of the presented method by solving a large-scale real-world problem instance provided by our industry partner DB Cargo Polska S.A., as well as a set of derived realistic instances.</div></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100145"},"PeriodicalIF":2.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561283","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}
Pub Date : 2024-01-01DOI: 10.1016/j.ejtl.2024.100130
Yijie Su , Hadi Ghaderi , Hussein Dia
Cities around the globe face major last mile delivery (LMD) challenges as a result of surging online commerce activity, increased parcel delivery demands, lack of parking capacity, and severe traffic congestion particularly in inner city areas. Although a number of innovative solutions and pathways have been proposed to address these challenges, their full impacts are still not well understood due to the lack of comprehensive field studies and real-world data on their performance. Traffic simulation techniques, which are widely used to model and evaluate the impacts of a wide range of urban mobility interventions, offer opportunities to investigate the impacts of city logistics interventions. However, research evidence on this topic remains fragmented, hindering constructive analysis of the role of traffic simulation and modelling in shaping sustainable urban delivery interventions. Given the growing research interest in the nexus of traffic simulation and city logistics, this paper aims to identify and evaluate primary studies related to the simulation forms, evolution, effectiveness, and their feasibility in evaluating the impacts of urban delivery interventions. The paper achieves this through a holistic systematic review that consolidates diverse perspectives on the topic. The paper analysed 79 articles, published by December 2023, that have used traffic simulation to model and evaluate a wide range of city logistics interventions. The review identified five main themes in the literature surrounding development and applications of traffic simulation, namely their use in evaluating the role of information and communication technologies, evaluations of advances in types and forms of delivery vehicles, their application in supporting policy interventions, evaluations of innovations in city logistics facilities and impacts of the collaborative economy. The review also helped in gaining insights about urban delivery interventions and their impacts as stand-alone or in combination with other solutions. The analysis confirms the validity and versatility of traffic simulation as an approach to model the impacts of urban delivery interventions on traffic flow, delivery service and customers, but also the sustainability implications of interventions. The paper also provides a future research agenda to guide future studies in developing and evaluating applications of various interventions with the leverage of traffic simulation.
{"title":"The role of traffic simulation in shaping effective and sustainable innovative urban delivery interventions","authors":"Yijie Su , Hadi Ghaderi , Hussein Dia","doi":"10.1016/j.ejtl.2024.100130","DOIUrl":"10.1016/j.ejtl.2024.100130","url":null,"abstract":"<div><p>Cities around the globe face major last mile delivery (LMD) challenges as a result of surging online commerce activity, increased parcel delivery demands, lack of parking capacity, and severe traffic congestion particularly in inner city areas. Although a number of innovative solutions and pathways have been proposed to address these challenges, their full impacts are still not well understood due to the lack of comprehensive field studies and real-world data on their performance. Traffic simulation techniques, which are widely used to model and evaluate the impacts of a wide range of urban mobility interventions, offer opportunities to investigate the impacts of city logistics interventions. However, research evidence on this topic remains fragmented, hindering constructive analysis of the role of traffic simulation and modelling in shaping sustainable urban delivery interventions. Given the growing research interest in the nexus of traffic simulation and city logistics, this paper aims to identify and evaluate primary studies related to the simulation forms, evolution, effectiveness, and their feasibility in evaluating the impacts of urban delivery interventions. The paper achieves this through a holistic systematic review that consolidates diverse perspectives on the topic. The paper analysed 79 articles, published by December 2023, that have used traffic simulation to model and evaluate a wide range of city logistics interventions. The review identified five main themes in the literature surrounding development and applications of traffic simulation, namely their use in evaluating the role of information and communication technologies, evaluations of advances in types and forms of delivery vehicles, their application in supporting policy interventions, evaluations of innovations in city logistics facilities and impacts of the collaborative economy. The review also helped in gaining insights about urban delivery interventions and their impacts as stand-alone or in combination with other solutions. The analysis confirms the validity and versatility of traffic simulation as an approach to model the impacts of urban delivery interventions on traffic flow, delivery service and customers, but also the sustainability implications of interventions. The paper also provides a future research agenda to guide future studies in developing and evaluating applications of various interventions with the leverage of traffic simulation.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100130"},"PeriodicalIF":2.4,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000050/pdfft?md5=153f2eeaae2dedbd9d5892150aafc08e&pid=1-s2.0-S2192437624000050-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140125317","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}
Crowdshipping is a new delivery paradigm that exploits the capacity of ordinary people who offer their own vehicles and free time to perform deliveries against compensation. In this work, we consider a peer-to-peer logistic platform where a company receives orders from its customers and assigns them to occasional drivers (ODs), or crowdshippers, who perform the delivery operations. We first investigate the problem of deciding how the orders should be partitioned into bundles, where a bundle is a set of orders assigned to the same OD. Then, we focus on the problem of determining the compensation associated with each bundle, with the purpose of minimizing the total delivery costs. The pricing scheme is based on the assumption that each OD is associated with a willingness-to-serve function, which is modeled as a random variable that gives the probability that the OD accepts to deliver the bundle given the compensation value. This random variable captures the estimation of the willingness-to-serve function that the company has elaborated, for example on the basis of historical data. If the compensation offered by the company is greater than or equal to the willingness-to-serve value, the OD performs the delivery, otherwise she/he refuses. In case no OD is available to deliver a bundle, then all packages in the bundle are offered to a third-party delivery company. We simulate two auction systems for the assignment of bundles to ODs: a static and a dynamic auction. In exhaustive simulation tests, we compare different pricing schemes as well as the two auction systems, and outline several managerial insights.
众包送货是一种新的送货模式，它利用普通人的能力，让他们提供自己的车辆和空闲时间，进行有偿送货。在这项工作中，我们考虑了一个点对点物流平台，在这个平台上，一家公司接收客户的订单，并将其分配给临时司机（OD）或众包送货员，由他们执行送货操作。我们首先研究的问题是决定如何将订单划分为捆绑订单，其中捆绑订单是指分配给同一 OD 的一组订单。然后，我们重点研究确定与每个捆绑相关的补偿问题，目的是最大限度地降低总配送成本。定价方案基于这样一个假设，即每个 OD 都与服务意愿函数相关联，该函数被建模为一个随机变量，给出了 OD 在给定补偿值的情况下接受交付捆绑订单的概率。该随机变量反映了公司对服务意愿函数的估计，例如根据历史数据进行的估计。如果公司提供的补偿大于或等于服务意愿值，则外包商执行交付，否则拒绝交付。如果没有 OD 可以递送捆绑包裹，那么捆绑包裹中的所有包裹都会提供给第三方递送公司。我们模拟了两种将包裹分配给 OD 的拍卖系统：静态拍卖和动态拍卖。在详尽的模拟测试中，我们对不同的定价方案以及两种拍卖系统进行了比较，并概述了一些管理见解。
{"title":"Bundles generation and pricing in crowdshipping","authors":"Giusy Macrina , Claudia Archetti , Francesca Guerriero","doi":"10.1016/j.ejtl.2024.100142","DOIUrl":"10.1016/j.ejtl.2024.100142","url":null,"abstract":"<div><p>Crowdshipping is a new delivery paradigm that exploits the capacity of ordinary people who offer their own vehicles and free time to perform deliveries against compensation. In this work, we consider a peer-to-peer logistic platform where a company receives orders from its customers and assigns them to occasional drivers (ODs), or crowdshippers, who perform the delivery operations. We first investigate the problem of deciding how the orders should be partitioned into bundles, where a bundle is a set of orders assigned to the same OD. Then, we focus on the problem of determining the compensation associated with each bundle, with the purpose of minimizing the total delivery costs. The pricing scheme is based on the assumption that each OD is associated with a <em>willingness-to-serve</em> function, which is modeled as a random variable that gives the probability that the OD accepts to deliver the bundle given the compensation value. This random variable captures the estimation of the <em>willingness-to-serve</em> function that the company has elaborated, for example on the basis of historical data. If the compensation offered by the company is greater than or equal to the <em>willingness-to-serve</em> value, the OD performs the delivery, otherwise she/he refuses. In case no OD is available to deliver a bundle, then all packages in the bundle are offered to a third-party delivery company. We simulate two auction systems for the assignment of bundles to ODs: a static and a dynamic auction. In exhaustive simulation tests, we compare different pricing schemes as well as the two auction systems, and outline several managerial insights.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100142"},"PeriodicalIF":2.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000177/pdfft?md5=c5cefe6620309fb3b6c6fb0260aced5a&pid=1-s2.0-S2192437624000177-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142021465","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}
Pub Date : 2024-01-01DOI: 10.1016/j.ejtl.2024.100141
Chungjae Lee , Kevin Dalmeijer , Pascal Van Hentenryck , Peibo Zhang
Autonomous trucks are expected to fundamentally transform the freight transportation industry. In particular, Autonomous Transfer Hub Networks (ATHNs), which combine autonomous trucks on middle miles with human-driven trucks on the first and last miles, are seen as the most likely deployment pathway for this technology. This paper presents a framework to optimize ATHN operations and evaluate the benefits of autonomous trucking. By exploiting the problem structure, this paper introduces a flow-based optimization model for this purpose that can be solved by blackbox solvers in a matter of hours. The resulting framework is easy to apply and enables the data-driven analysis of large-scale systems. The power of this approach is demonstrated on a system that spans all of the United States over a four-week horizon. The case study quantifies the potential impact of autonomous trucking and shows that ATHNs can have significant benefits over traditional transportation networks.
{"title":"Optimizing Autonomous Transfer Hub Networks: Quantifying the potential impact of self-driving trucks","authors":"Chungjae Lee , Kevin Dalmeijer , Pascal Van Hentenryck , Peibo Zhang","doi":"10.1016/j.ejtl.2024.100141","DOIUrl":"10.1016/j.ejtl.2024.100141","url":null,"abstract":"<div><p>Autonomous trucks are expected to fundamentally transform the freight transportation industry. In particular, Autonomous Transfer Hub Networks (ATHNs), which combine autonomous trucks on middle miles with human-driven trucks on the first and last miles, are seen as the most likely deployment pathway for this technology. This paper presents a framework to optimize ATHN operations and evaluate the benefits of autonomous trucking. By exploiting the problem structure, this paper introduces a flow-based optimization model for this purpose that can be solved by blackbox solvers in a matter of hours. The resulting framework is easy to apply and enables the data-driven analysis of large-scale systems. The power of this approach is demonstrated on a system that spans all of the United States over a four-week horizon. The case study quantifies the potential impact of autonomous trucking and shows that ATHNs can have significant benefits over traditional transportation networks.</p></div>","PeriodicalId":45871,"journal":{"name":"EURO Journal on Transportation and Logistics","volume":"13 ","pages":"Article 100141"},"PeriodicalIF":2.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2192437624000165/pdfft?md5=50e7f65a716bd9bab7d80ed2f378b9a5&pid=1-s2.0-S2192437624000165-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141984797","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号