Transportation Research Part E-Logistics and Transportation Review最新文献

{"title":"Effects of high-speed rail on intercity travels, utility and social welfare in urban agglomerations: A game-theoretic perspective","authors":"Han Wang,&nbsp;Hai-Jun Huang","doi":"10.1016/j.tre.2024.103800","DOIUrl":"10.1016/j.tre.2024.103800","url":null,"abstract":"<div><div>This paper investigates the effects of newly built high-speed rail on urban performances in terms of intercity travels, utility and social welfare by extending the two-city system into a representative urban agglomeration system consisting of a hub city and two peripheral cities. A framework based on the Cournot model with three interacted games is developed to characterize competitions among HSR operators in the system. Introducing HSR between peripheral cities decentralizes the intercity travel demands from the hub city to peripheral cities, and it does not always induce more that for the urban agglomeration. We find that “weight” on social welfare, substitutability, gross benefits ratio, HSR accessibility and frequency would differentially impact the hub and peripheral cities. Numerical examples and a case study incorporating all factors based on Central Plains Urban Agglomeration in China are conducted to illustrate the model, together with some policy implications.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robotic warehouse systems considering dynamic priority","authors":"Zhengmin Zhang ,&nbsp;Yeming Gong ,&nbsp;Zhe Yuan ,&nbsp;Wanying Chen","doi":"10.1016/j.tre.2024.103779","DOIUrl":"10.1016/j.tre.2024.103779","url":null,"abstract":"<div><div>The research proposes a new methodological framework based on dynamic priority to handle different order classes in robotic warehouse systems. Traditional static priority methods in facility logistics may cause low-priority orders to experience excessive delays and fail to ensure fairness. Our dynamic priority approach addresses this fairness issue by adjusting priorities over time to fulfill orders within promised times, ensuring both high-priority orders and long-waiting low-priority orders receive timely attention. We present stochastic models of dynamic priority queueing networks to describe warehouse systems and estimate throughput times. Experiments validate the analytical stochastic models, and experimental results indicate that the dynamic priority model achieves shorter delay times than the static priority model and the FCFS model. We propose design insights based on experimental results and provide an approach to select the optimal robot number. Furthermore, by employing a fairness index, we develop a new decision support tool for determining warehouse configurations with requested performance objectives. Experimental results demonstrate that dynamic priority can ensure fairness across a wider range of scenarios. Additionally, with insufficient pickers, the system performs better with the put wall than without it.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and regulating a ride-sourcing market integrated with vehicle rental services","authors":"Dong Mo ,&nbsp;Hai Wang ,&nbsp;Zeen Cai ,&nbsp;W.Y. Szeto ,&nbsp;Xiqun (Michael) Chen","doi":"10.1016/j.tre.2024.103797","DOIUrl":"10.1016/j.tre.2024.103797","url":null,"abstract":"<div><div>With the popularity of on-demand ride services worldwide, ride-sourcing platforms must maintain an adequate fleet size and cope with growing travel demand. Recently, platforms have attempted to provide vehicle rental services to drivers who do not own cars, then recruited them to provide on demand ride services. This helps lower the entry barrier for drivers and offers another profitable business for platforms. From the government’s perspective, however, it is challenging to coordinately regulate a ride-sourcing business and vehicle rental business. This paper proposes a bi-level optimization model to investigate how the government regulates the ride-sourcing market integrated with vehicle rental services. Specifically, how the government designs regulatory policies for minimum driver wage and maximum vehicle rental fee at the upper level, and how a monopoly profit-oriented platform optimizes riders’ price, drivers’ wage, and vehicle rental fee at the lower level. We derive an analytical phase diagram for the two policies and present the government’s decisions in five mutually exclusive regions with respect to regulatory effects, i.e., ineffective region, minimum-driver-wage-effective region, maximum-rental-fee-effective region, coordinated policy region, and infeasible region. Our theoretical and numerical results indicate that the government should precisely coordinate the two policies to achieve higher total social welfare, i.e., the weighted sum of rider surplus, driver surplus, and platform profit. We also prove that if the weights of all stakeholders in social welfare are equal, the platform’s vehicle rental business will achieve zero profit when the total social welfare is maximized. The proposed model and analytical results generate managerial insights and provide suggestions for government regulation and platform operations management in the ride-sourcing market integrated with vehicle rental services.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Store brand entry with asymmetric cost information","authors":"Yuanyuan Luo ,&nbsp;Xiaojie Sun ,&nbsp;Xiaohang Yue","doi":"10.1016/j.tre.2024.103790","DOIUrl":"10.1016/j.tre.2024.103790","url":null,"abstract":"<div><div>This study conducts research on a dominant retailer’s establishment strategy of a store brand in a supply chain, in which the retailer possesses private knowledge of the store brand’s product cost, while the manufacturer is only informed about the distribution of this cost information. The store brand entry with asymmetric information initiates a signaling game between the chain members. Through comparing equilibrium outcomes, we find that the pooling equilibrium consistently prevails as the dominant equilibrium, suggesting that the informed retailer is reluctant to reveal the cost information to her national brand cooperative manufacturer. We also explore the influence of a retailer’s store brand entry on the national-brand manufacturer’s performance. The findings reveal that, with asymmetric cost information, mutually beneficial outcomes for all parties involved can be achieved by the establishment of a store brand. Furthermore, we delve into how the asymmetric cost information affects the performance of the chain members. Surprisingly, our findings demonstrate that asymmetric cost information may be desirable not only for the retailer, but also for the less informed manufacturer under specific circumstances. This suggests the possibility of supply chain members reaching a mutual agreement on the structure of asymmetric cost information.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the impact of late deliveries on the operations of the crowd-shipping platform: A mean-variance analysis","authors":"Qilong Li ,&nbsp;Haohan Xiao ,&nbsp;Min Xu ,&nbsp;Ting Qu","doi":"10.1016/j.tre.2024.103793","DOIUrl":"10.1016/j.tre.2024.103793","url":null,"abstract":"<div><div>Accompanying the booming of e-commerce, crowd-shipping (CS) service has gained much attention recently. It outsources shipping tasks to the crowd with app-based platform technologies, which largely increases shipping capacities. Despite its merits in providing flexible options for consignees, CS services often face difficulties in delivering packages on time due to several reasons such as crowdshippers’ unprofessional skills, which can be regarded as one of the risks in the CS platform’s operations. Motivated by this, we adopt a mean–variance (MV) approach to characterize the CS platform’s behaviors towards late deliveries, in which two kinds of risk-related behaviors, i.e., risk-neutral and risk-averse attitudes, are incorporated. To identify the impact of late deliveries on the CS platform’s operations, we propose two MV-based risk models, i.e., the risk-neutral and risk-averse models. Equilibrium results concerning the shipping price, the service level, the platform’s expected profit, the consignees’ surplus, and social welfare can be derived from the two models. Results show that late deliveries will negatively affect the CS platform’s profit but positively affect the CS market demand. Policy implications concerning offsetting the negative impact of late deliveries are further proposed and discussed.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing a carbon-trading incentive scheme for mode shifts in multi-modal transport systems","authors":"Bing Liu ,&nbsp;Xiaolei Ma ,&nbsp;Wei Liu ,&nbsp;Zhenliang Ma","doi":"10.1016/j.tre.2024.103789","DOIUrl":"10.1016/j.tre.2024.103789","url":null,"abstract":"<div><div>The pressing need to reduce greenhouse gas emissions triggers the imperative for efficient travel demand management. Previous studies have explored budget-based and aggregated incentive programs, which place a significant financial burden on governments and tend to be limited in contributing to effective behavior change in practice due to budget issues. This study proposes a personal carbon trading travel incentive (PCTTI) mechanism, to encourage private car commuters shifting to using public transit. The incentive budget for PCTTI is sourced from the revenue generated through selling carbon emission reductions resulting from commuters’ travel mode shifts. To determine the optimal incentives, we developed an incentive scheme optimization model based on the Stackelberg game model. Numerical analysis reveals the significant potential of the PCTTI to reduce carbon emissions and travel costs across various scenarios within a multi-modal transportation system. This potential is evident amidst changes in the fixed costs of car travel, carbon trading prices, the use of different travel modes, the value of time, and the prevalence of electric vehicles. The advantages are most pronounced when the carbon trading price exceeds 40 CNY/ton, and when the usage of public transit, the value of time, and the proportion of electric vehicles each fall below 0.4, 50 CNY/hour, and 0.4, respectively.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collaboration and resource sharing in the multidepot time-dependent vehicle routing problem with time windows","authors":"Yong Wang ,&nbsp;Zikai Wei ,&nbsp;Siyu Luo ,&nbsp;Jingxin Zhou ,&nbsp;Lu Zhen","doi":"10.1016/j.tre.2024.103798","DOIUrl":"10.1016/j.tre.2024.103798","url":null,"abstract":"<div><div>Concerns about energy conservation and emission reduction have highlighted the importance of environmentally sound logistics networks in urban areas. These networks are deeply intertwined with urban traffic systems, where variations in transit speeds can significantly increase the energy consumption and carbon emissions of delivery vehicles, compromising the environmental sustainability of urban deliveries. To address this, we propose a multidepot time-dependent vehicle routing problem with time windows, enhancing route planning flexibility and resource configuration. Our approach begins with a route spatiotemporal decomposition method to estimate vehicle travel times and emissions based on varying vehicle speeds. We then develop a multiobjective mixed integer linear programming model that aims to minimize total operating costs, the number of vehicles, and carbon dioxide emissions. A hybrid heuristic algorithm combining spectral clustering, multiobjective ant colony optimization, and variable neighborhood search is proposed to solve the model. This algorithm incorporates collaboration and resource sharing strategies, a pheromone initialization mechanism, a novel heuristic operator that accounts for time dependency, and a self-adaptive update mechanism, enhancing both solution quality and algorithm convergence. We compare the performance of our algorithm with that of the CPLEX solver, multiobjective ant colony optimization, non-dominated sorting genetic algorithm-Ⅲ, and multiobjective particle swarm optimization. The results demonstrate the superior convergence, uniformity, and spread of our proposed algorithm. Furthermore, we apply our model and algorithm to a real-world case in Chongqing, China, analyzing optimized results for different time intervals and vehicle speeds. This study offers robust methodologies for theoretically and practically addressing the multidepot time-dependent vehicle routing problem with time windows, contributing to the development of economical, efficient, collaborative, and sustainable urban logistics networks.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning-based Pareto-optimum routing of ships incorporating uncertain meteorological and oceanographic forecasts","authors":"Yuhan Guo ,&nbsp;Yiyang Wang ,&nbsp;Yuhan Chen ,&nbsp;Lingxiao Wu ,&nbsp;Wengang Mao","doi":"10.1016/j.tre.2024.103786","DOIUrl":"10.1016/j.tre.2024.103786","url":null,"abstract":"<div><div>In modern shipping logistics, multi-objective ship route planning has attracted considerable attention in both academia and industry, with a primary focus on energy conservation and emission reduction. The core challenges in this field involve determining the optimal route and sailing speed for a given voyage under complex and variable meteorological and oceanographic conditions. Typically, the objectives revolve around optimizing fuel consumption, carbon emissions, duration time, energy efficiency, and other relevant factors. However, in the multi-objective route planning problem involving variable routes and speeds, the extensive solution space contains a substantial number of unevenly distributed feasible samples. Traditional heuristic optimization techniques, such as multi-objective evolutionary algorithms, which serve as the core component of optimization programs, suffer from inefficiencies in exploring the solution space. Consequently, these algorithms may tend to converge toward local optima during population iteration, resulting in a solution set characterized by sub-optimal convergence and limited diversity. This ultimately undermines the potential benefits of routing optimization. To address such challenging problem in route planning tasks, we propose a self-adaptive intelligent learning network aiming at capturing the potential evolutionary characteristics during population iteration, in order to achieve high-efficiency directed optimization of individuals. Additionally, an uncertainty-driven module is developed by incorporating ensemble forecasts of meteorological and oceanographic variables to form the Pareto frontier with more reliable solutions. Finally, the overall framework of the proposed learning-based multi-objective evolutionary algorithm is meticulously designed and validated through comprehensive analyses. Optimization results demonstrate its superiority in generating routing plans that effectively minimize costs, reduce emissions, and mitigate risks.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142329862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pricing and unauthorized channel strategies for a global manufacturer considering import taxes","authors":"Xiaohui Yu ,&nbsp;Tiaojun Xiao ,&nbsp;Georges Zaccour","doi":"10.1016/j.tre.2024.103784","DOIUrl":"10.1016/j.tre.2024.103784","url":null,"abstract":"<div><div>Global manufacturers face a pricing dilemma: setting higher prices in foreign markets to offset import taxes may lead to unauthorized cross-border channels; while narrowing price differences between domestic and foreign markets to block these channels increases the tax burden. To address this challenge, we develop Stackelberg game models to investigate the pricing and unauthorized channel strategy for a global manufacturer. Our findings indicate that an unauthorized channel can benefit the manufacturer by providing a means to avoid import taxes and potentially increasing overall demand in the foreign market. When the impact of an unauthorized channel on brand reputation is low, the manufacturer should widen the price difference between domestic and foreign markets to allow it. Conversely, when facing high brand reputation risks, the manufacturer must consider the import tax in the foreign market. If the import tax is high, the manufacturer should narrow the price difference between domestic and foreign markets to block the unauthorized channel; otherwise, simply ignore the threat of the unauthorized channel and maintain regular prices. We also examine the effects of consumer acceptance of gray market products and import tax incentives for cross-border e-commerce. We find that an increase in the two factors enhances the manufacturer’s inclination to allow an unauthorized channel. Our results remain robust across varying import tax structures, production costs, consumer valuations, and exchange rates, as well as when there are differences in market potential and consumer valuation between domestic or foreign markets.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142329863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Safety aware neural network for connected and automated vehicle operations","authors":"Handong Yao ,&nbsp;Xiaopeng Li ,&nbsp;Qianwen Li ,&nbsp;Chenyang Yu","doi":"10.1016/j.tre.2024.103780","DOIUrl":"10.1016/j.tre.2024.103780","url":null,"abstract":"<div><div>Contemporary research in connected and automated vehicle (CAV) operations typically segregates trajectory prediction from planning in two segregated models. Trajectory prediction narrowly focuses on reducing prediction errors, disregarding the implications for subsequent planning. As a result, CAVs adhering to trajectories planned based on such predictions may collide with surrounding traffic. To mitigate such vulnerabilities, this study introduces a holistic safety-aware neural network (SANN) framework, representing a paradigm shift by integrating trajectory prediction and planning into a cohesive model. The SANN architecture incorporates prediction and planning layers, leveraging existing neural networks for prediction and introducing novel recurrent neural cells embedded with car-following dynamics for planning. The prediction layers are regulated by the CAV trajectory planning performance including safety, mobility, and energy efficiency. A key innovation of the SANN lies in its approach to safety regulation, which is based on actual, rather than forecasted, traffic movements. By applying time geography theory, it assesses CAV motion feasibility, setting limits on speed and acceleration for safety in line with actual traffic patterns. This feasibility analysis results are integrated into the neural loss function as a penalty factor, steering the optimization process towards safer CAV operations. The efficacy of the SANN is enhanced by employing the sequential unconstrained minimization technique, which enables the fine-tuning of penalty weights, thereby producing more robust solutions. Empirical evaluations, comparing the holistic SANN with conventional segregated models, demonstrate its superior performance. The SANN achieves substantial enhancements in safety and energy efficiency, with only a marginal compromise on mobility. This success underscores the significance of integrating machine learning with domain knowledge (operations research and traffic flow theory) for safer and more environmentally friendly CAV operations.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}