The container drayage problem for heterogeneous trucks with multiple loads: A revisit

Chen, Rui; Chen, Shukai; Cui, Haipeng; Meng, Qiang

doi:10.1016/j.tre.2021.102241

Cited by 14 publications

(1 citation statement)

References 27 publications

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“…The latter concept makes this approach popular for Dial-a-Ride problems, for example, Detti et al [33] and Muelas [45,46]. Souza et al [47], Chen et al [48], and Kaleche et al [49] also successfully applied this approach in combination with other search methods.…”

Section: Heuristic Algorithms For Dial-a-ride Problemsmentioning

confidence: 99%

Application of Generative Adversarial Network to Optimize Vehicle Allocation at Dispatch Stations of Paratransit Services

et al. 2022

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As aging populations increase worldwide, many governments have introduced the concept of paratransit services to assist individuals with limited mobility with transportation. A successful paratransit service must be able to satisfy most requests to the system; this success is typically related to the allocation of vehicles to dispatch stations. A suitable configuration can reduce unnecessary travel time and thus serve more people. This resembles the classic Dial-a-Ride problem, which previous studies have solved using heuristic algorithms. Most of these algorithms, however, incur heavy computational costs and, therefore, cannot be operated online, especially when there are many conditions to consider, many configuration requirements, or many vehicles requested. Therefore, this paper proposes an approach based on the generative adversary network (GAN), which can reduce computation significantly. In online environments, this approach can be implemented in just a few seconds. Furthermore, the amount of computation is not affected by the number of conditions, configuration requirements, or vehicles requested. This approach is based on three important concepts: (1) designing a GAN to solve the target problem; (2) using an improved Voronoi diagram to divide the overall service area to generate the input of the GAN generator; (3) using well-known system simulation software Arena to swiftly generate many conditions for the target problem and their corresponding best solutions to train the GAN. The efficiency of the proposed approach was verified using a case study of paratransit services in Yunlin, Taiwan.

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Section: Heuristic Algorithms For Dial-a-ride Problemsmentioning

confidence: 99%

Application of Generative Adversarial Network to Optimize Vehicle Allocation at Dispatch Stations of Paratransit Services

et al. 2022

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The dynamic stochastic container drayage problem with truck appointment scheduling

Stoop,

Pickavet,

Colle

et al. 2024

OR Spectrum

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Environmental challenge of vehicle dispatching in marine container drayage

Nishimura,

Papadimitriou,

Shintani

et al. 2024

Ann Oper Res

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In marine container drayage (CD), which refers to the transport of goods over a short distance, empty containers (ECs) are required to be transported long distances between a terminal and a shipper/consignee by conventional transportation. This causes truck traffic congestion in harbor districts that increases CO2 emissions (CO2EM). This study addresses the vehicle dispatch problem with respect to the environmental impact of marine CD, considering the tractor dwell time is long at the customer site due to cumbersome container loading/unloading (L/U). We model this problem as an extended version of the vehicle routing problem with precedence constraints to minimize the total CO2 weighted travel distance. To improve CD operation in long L/U time, we propose a new practice for CD operations. Additionally, we develop a mixed integer programing model (MIP) for the new practice representation, and propose a Simulated Annealing (SA) based heuristic approach to solving the new practice instance. By implementing our proposed new operation, in a long L/U time, the CO2EM, EC move and number of tractors required can also be reduced by allowing uncoupled tractor move.

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The container drayage problem for heterogeneous trucks with multiple loads: A revisit

Cited by 14 publications

References 27 publications

Application of Generative Adversarial Network to Optimize Vehicle Allocation at Dispatch Stations of Paratransit Services

Application of Generative Adversarial Network to Optimize Vehicle Allocation at Dispatch Stations of Paratransit Services

The dynamic stochastic container drayage problem with truck appointment scheduling

Environmental challenge of vehicle dispatching in marine container drayage

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