EURO Journal on Transportation and Logistics

Journal Information
ISSN / EISSN : 2192-4376 / 2192-4384
Published by: Elsevier BV (10.1016)
Total articles ≅ 188
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, Jens Lysgaard
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100054

Abstract:
This paper addresses a school bus routing problem, which is classified as a location–allocation-routing problem. The problem consists of selecting pickup locations, allocating students to them, and generating a route that traverses between them. The proposed model is for a single school and a single-route. The objective is to find the subset of pickup stops aiming to minimize the total distance walked by all students from their homes to the respective pickup stops, subject to an upper bound on the route distance of connecting selected stops. We present an exact and heuristic algorithms which are developed based on a layered graph. Computational results are conducted on a series of generated benchmark instances and test data from Norway that demonstrate a good performance of the proposed approach.
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100047

Abstract:
The possible unavailability of urban rail-based transport services due to planned maintenance activities may have significant consequences on the perceived quality of service, thus affecting railway attractiveness.
EURO Journal on Transportation and Logistics; https://doi.org/10.1016/j.ejtl.2021.100049

Abstract:
The transition from traditional fuel-based bus transportation towards electric bus systems is regarded as a beacon of hope for emission-free public transport. In this study, we focus on battery electric bus systems, in which charging is possible at a variety of locations distributed at terminal stations over the entire bus network. In such systems, two intertwined planning problems to be considered are charging location planning and electric vehicle scheduling. We account for the interdependent nature of both planning problems by adopting a simultaneous optimization perspective. Acknowledging the existence of parameter uncertainty in such complex planning situations, which is rooted in potential changes of values of several environmental factors, we analyze the solution sensitivity to several of these factors in order to derive methodological guidance for decision makers in public transportation organizations. Based on the formulation of a new mathematical model and the application of a variable neighborhood search metaheuristic, we conduct sensitivity analysis by means of numerical experiments drawing on real-world data. The experiments reveal that it is not possible to identify persistent structures for charging locations by an a priori analysis of the problem instances, so that rather a simultaneous optimization is necessary. Furthermore, the experiments show that the configuration of electric bus systems reacts sensitively to parameter changes.
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100050

Abstract:
The inventory routing problem (IRP) is an optimisation problem that integrates transportation and inventory management decisions. When subjected to unexpected events such as demand changes, the a posteriori approach consists in re-optimising including the data related to this event; the challenge is to ensure that the obtained solution does not deviate too much from the original one, lest that creates important organisational issues. Therefore, a stability metric is needed when re-optimising IRP models. This article proposes a panel of stability metrics adapted from the scheduling, routing and inventory management literature to fit the requirements of the IRP and proposes mathematical formulations for the most relevant ones. A framework of comparison is proposed to validate and compare these metrics over a benchmark of 3000 instances generated from the literature. A strong correlation between the metrics is observed. Moreover, the results show that ensuring the stability of the re-optimised solutions has little impact on the initial objective, the total cost.
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100052

Abstract:
Liner shipping repositioning is the costly process of moving container ships between services in a liner shipping network to adjust the network to the changing demands of customers. Existing deterministic models for the liner shipping fleet repositioning problem (LSFRP) ignore the inherent uncertainty present in the input parameters. Assuming these parameters are deterministic could lead to extra costs when plans computed by a deterministic model are realized. We introduce an optimization model for the stochastic LSFRP that handles uncertainty regarding container demands and ship travel times. We extend existing LSFRP instances with uncertain parameters and use this new dataset to evaluate our model. We demonstrate the influence of uncertain demand and travel times on the resulting repositioning plans. Furthermore, we show that stochastic optimization generates solutions yielding up to ten times higher expected values and more robust solutions, measured against the CVaR90 objective, for decision-makers in the liner shipping industry compared to the application of deterministic optimization in the literature.
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100046

Abstract:
Service network design is an important optimization problem for intermodal freight transportation on a tactical level. It includes the decisions on choosing transportation modes and paths for commodities throughout the intermodal network. We present a stochastic service network design model with an integrated vehicle routing problem (SSND-VRP), which simultaneously covers transportation service choice and tour planning decisions for road transportation under consideration of uncertain transportation times. A sample average approximation approach is combined with an iterated local search in order to solve problem instances in a real-world case study for three intermodal road-rail networks in Central Europe. Results of the SSND-VRP are compared with its expected value model and a successive planning approach, demonstrating the possible cost reductions and the decrease in missed intermodal services that are achieved by the integrated stochastic model. In further parameter variation experiments we show that the attractiveness of rail transportation is highly sensitive to changes in intermodal costs, whereas the impact of delay reductions of the railway services is relatively low.
Qi Luo, Shukai Li,
EURO Journal on Transportation and Logistics; https://doi.org/10.1016/j.ejtl.2021.100045

Abstract:
Mobility-on-Demand Transit (MoDT) is a suitable solution for linking packed urban centers to low-demand suburban areas. Meanwhile, micromobility services, including dockless bikesharing and electric scooters, are growing exponentially worldwide, providing a low-cost, low-emission travel mode for short home-based trips. We propose an intermodal network in which travelers use micromobility for the first-/last-mile connections to MoDT. The optimal design of the intermodal network is formulated as a two-stage stochastic program with a revenue-maximization objective. The first stage solves the near-optimal transfer hub locations, and the second stage considers the integrated operations of the micromobility and MoDT vehicle fleet. This work contributes to the MoD literature by addressing how to coordinate the intermodal transfers and improve the utilization of vehicles with uncertain demand. The movements of these vehicles are modeled as an interconnected closed queueing network with time lags. A new starter-follower model captures the rearranged ride-pooling behavior at these selected transfer hubs. We implement this network design method to evaluate the benefit of combining a bikesharing and a MoDT network in New York City. This paper provides a systematic method for designing intermodal mobility networks, laying the foundation for multimodal mobility applications.
M. SteadieSeifi, ,
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100044

Abstract:
We study the planning of a multi-modal transportation system with perishable products, demand uncertainty and repositioning of the empty Returnable Transport Items (RTIs). We propose a rolling horizon framework where we periodically re-optimize. As such, relevant responses and actions to new occurred demand are taken, and possible updates to the transportation and repositioning plans can be made. Our rolling horizon framework considers the uncertainty of customer demand, formulated as a Scenario-based Two-Stage Program (STSP) for which a set of scenarios is generated. An Adaptive Large Neighborhood Search (ALNS) algorithm is used to solve this scenario-based problem. Our proposed ALNS algorithm employs new operators and strategies to solve this complex and large problem. We give detailed computational analysis on the properties of our framework, evaluating the effects of stochastic demand, and we provide practical insights.
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100042

Abstract:
This paper proposes different algorithms to tackle the Generalized Train Unit Shunting Problem (G-TUSP). This is the pre-operational problem of managing rolling stock in a station, between arrivals and departures. It includes four sub-problems: the Train Matching Problem, the Track Assignment Problem, the Shunting Routing Problem, and the Shunting Maintenance Problem. In our algorithms, we consider different combinations for the integrated or sequential solutions of these sub-problems, typically considered independently in the literature. We assess the performance of the algorithms proposed in real-life and fictive instances representing traffic in Metz-Ville station, which includes four shunting yards. It is a main junction between two dense traffic lines in the east of France. In a thorough experimental analysis, we study the contribution of each sub-problem to the difficulty of the G-TUSP, and we identify the best algorithms. The outcomes of our algorithms are superior to solutions manually designed by experienced railway practitioners.
EURO Journal on Transportation and Logistics, Volume 10; https://doi.org/10.1016/j.ejtl.2021.100043

Abstract:
Overloaded axles not only lead to increased erosion on the road surface, but also to an increased braking distance and more serious accidents due to higher impact energy. Therefore, the load on axles should be already considered during the planning phase and thus before loading the truck in order to prevent overloading. Hereby, a detailed 2D or 3D planning of the vehicle cargo space is required. We model the Axle Weight Constraint for trucks with and without trailers based on the Science of Statics and provide flexible formulas for different axle configurations of trucks. We include the Axle Weight Constraint into the combined Vehicle Routing and Container Loading Problem (“2L-CVRP” and “3L-CVRP”). A hybrid heuristic approach is used where an outer Adaptive Large Neighbourhood Search tackles the routing problem and an inner Deepest-Bottom-Left-Fill algorithm solves the packing problem. Moreover, to ensure feasibility, we show that the Axle Weight Constraint must be checked after each placement of an item. The impact of the Axle Weight Constraint is also evaluated.
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