Solution techniques for the inter-modal pickup and delivery problem in two regions

Dragomir, Alina; Doerner, Karl F.

doi:10.1016/j.cor.2019.104808

Cited by 7 publications

(2 citation statements)

References 23 publications

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“…They proved that the benefits arising from the coalition are bigger at the aggregate level than those which could be achieved in a non-cooperative system because stakeholders increase their efficiency by sharing resources, producing less pollution, and lowering transporting prices. Dragomir and Doerner (2020) decomposed a routing problem that transforms parcels between two cities into a three-part network structure and solved a pickup and delivery problem with long hauls without direct shipments between regions. The fixed-line part was a scheduled line, and the model met all capacity and timing constraints.…”

Section: Request Destinationmentioning

confidence: 99%

Optimization of Multimodal Dial-A-Ride Systems with Fixed-Line Flexible Time Schedules

Elgazzar,

Fors,

Ali

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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This paper investigates a multimodal system that integrates the general dial-a-ride problem with a set of fixed-line vehicles having a flexible schedule. The passenger trips are made in a three-stage journey using a dial-a-ride vehicle and a fixed-line bus. Passengers are picked up from an origin point and transferred to a collecting point via a dial-aride vehicle. Then, fixed-route buses transfer passengers to a second collecting point where another dial-a-ride vehicle will pick up and transfer them to their requested destination. The main objective of this integration is to reduce the total trip cost by carrying part of it through cheaper fixed-route service while maximizing the utilization of seats in the fixed-route vehicle. The model provides each fixed line with a suggested start time. A mixed-integer linear programming model was developed for the problem, and computational testing on small-size instances has been carried out to demonstrate the viability of the proposed system.

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Section: Request Destinationmentioning

confidence: 99%

Optimization of Multimodal Dial-A-Ride Systems with Fixed-Line Flexible Time Schedules

Elgazzar,

Fors,

Ali

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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“…Furthermore, multimodal transportation starts with the container pickup from the shipper and ends with container delivery to the receiver. Therefore, both pickup and delivery determine the time efficiency of the entire multimodal transportation process [15]. However, the majority of relevant studies focus more on the delivery than the pickup when modeling the time window and assume that containers are released at a fixed time [13,16] or there is the earliest release time [17].…”

Section: Introductionmentioning

confidence: 99%

Solving a Multimodal Routing Problem with Pickup and Delivery Time Windows under LR Triangular Fuzzy Capacity Constraints

Ge,

Sun

2024

Axioms

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This study models a container routing problem using multimodal transportation to improve its economy, timeliness, and reliability. Pickup and delivery time windows are simultaneously formulated in optimization to provide the shipper and the receiver with time-efficient services, in which early pickup and delayed delivery can be avoided, and nonlinear storage periods at the origin and the destination can be minimized. Furthermore, the capacity uncertainty of the multimodal network is incorporated into the advanced routing to enhance its reliability in practical transportation. The LR triangular fuzzy number is adopted to model the capacity uncertainty, in which its spread ratio is defined to measure the uncertainty level of the fuzzy capacity. Due to the nonlinearity introduced by the time windows and the fuzziness from the network capacity, this study establishes a fuzzy nonlinear optimization model for optimization problem. A chance-constrained linear reformulation equivalent to the proposed model is then generated based on the credibility measure, which makes the global optimum solution attainable by using Lingo software. A numerical case verification demonstrates that the proposed model can effectively solve the problem. The case analysis points out that the formulation of pickup and delivery time windows can improve the timeliness of the entire transportation process and help to achieve on-time transportation. Furthermore, improving the confidence level and the uncertainty level increases the total costs of the optimal route. Therefore, the shipper and the receiver must prepare more transportation budget to improve reliability and address the increasing uncertainty level. Further analysis draws some insights to help the shipper, receiver, and multimodal transport operator to organize a reliable and cost-efficient multimodal transportation under capacity uncertainty through confidence level balance and transportation service and transfer service selection.

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Green road–rail intermodal routing problem with improved pickup and delivery services integrating truck departure time planning under uncertainty: an interactive fuzzy programming approach

Sun

Nan

Huang

2021

Complex Intell. Syst.

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This paper addresses the multi-objective optimization for the road–rail intermodal routing problem that aims to minimize the total costs and carbon dioxide emissions of the routes. To achieve high timeliness of the entire transportation process, pickup and delivery services are simultaneously improved based on the employment of fuzzy soft time windows to measure their service levels. The modeling of road–rail intermodal routing considers fixed schedules of rail and time flexibility of road to match the real-world transportation scenario, in which travel times and carbon dioxide emission factors of road services are considered to be time-varying. To improve the feasibility of the routing, uncertainty of travel times and carbon dioxide emission factors of road services and capacities of rail services are incorporated into the problem. By applying trapezoidal fuzzy numbers to formulate the uncertainty, we propose a fuzzy multi-objective nonlinear optimization model for the routing problem that integrates the truck departure time planning for road services. After processing the model with fuzzy chance-constrained programming and linearization, we obtain an auxiliary equivalent crisp linear model and solve it by designing an interactive fuzzy programming approach with the Bounded Objective Function method. Based on an empirical case study, we demonstrate the validity of the proposed approach and discuss the effects of improving the confidence levels and service levels on the optimization results. The case analysis reveals several managerial insights that help to realize an efficient transportation organization by making effective trade-offs among lowering costs, reducing emissions, improving service levels, and enhancing feasibility.

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Solution techniques for the inter-modal pickup and delivery problem in two regions

Cited by 7 publications

References 23 publications

Optimization of Multimodal Dial-A-Ride Systems with Fixed-Line Flexible Time Schedules

Optimization of Multimodal Dial-A-Ride Systems with Fixed-Line Flexible Time Schedules

Solving a Multimodal Routing Problem with Pickup and Delivery Time Windows under LR Triangular Fuzzy Capacity Constraints

Green road–rail intermodal routing problem with improved pickup and delivery services integrating truck departure time planning under uncertainty: an interactive fuzzy programming approach

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