The Inland Container Transportation Problem with Separation Mode Considering Carbon Dioxide Emissions

He, Wei; Jin, Zhihong; Huang, Ying Jeh; Xu, Shida

doi:10.3390/su13031573

Cited by 10 publications

(4 citation statements)

References 49 publications

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“…Bomboi [34] modeled the stochastic CDP by considering stochastic travel times. He et al [35] devised a MILP model that considered carbon emissions and established an improved ant colony optimization algorithm. Yang et al [6] established a MILP model grounding in the arc flow framework and designed a novel GA for CDP involving a heterogeneous fleet.…”

Section: The Cdp Involving Trucking Operation Modes and Empty Contain...mentioning

confidence: 99%

Modeling and Optimization of Container Drayage Problem with Empty Container Constraints across Multiple Inland Depots

Yu,

Feng,

et al. 2024

Sustainability

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Container drayage involves the transportation of containers by trucks. Although the distance is relatively short compared to maritime and rail transport, container drayage accounts for 25% to 40% of the total container transportation costs and significantly contributes to increased fuel consumption and carbon emissions. Thus, the modeling of the container drayage problem (CDP) has received a lot of attention in the last two decades. However, the three fundamental modeling factors, including the combination of trucking operation modes and empty container relocation strategies, as well as empty container constraints and multiple inland depots, have not been simultaneously investigated. Hence, this study addressed a comprehensive CDP that simultaneously incorporates the three modeling factors. The problem was formulated as a novel mixed integer linear programming (MILP) model based on the DAOV graph. Given the complexity of this problem, it was not realistic to find an exact solution for large instances. Therefore, an improved genetic algorithm (GA) was designed by integrating the “sequential insertion” method and “solution re-optimization” operation. The performance of Gurobi and GA was validated and evaluated through randomly generated instances. The results indicate that (1) the proposed algorithm can provide near-optimal solutions for large-scale instances within a reasonable running time, (2) the greatest cost savings from combining trucking operation modes and empty container relocation strategies range from 10.45% to 31.86%, and (3) the three modeling factors significantly influence the fuel consumption and carbon emissions, which can provide managerial insights for sustainable container drayage practices.

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Section: The Cdp Involving Trucking Operation Modes and Empty Contain...mentioning

confidence: 99%

Modeling and Optimization of Container Drayage Problem with Empty Container Constraints across Multiple Inland Depots

Yu,

Feng,

et al. 2024

Sustainability

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“…Constraint (8) means that each transportation task is executed once. Constraint (9) and Constraint (10), respectively, specify the driving state of the tractor when carrying out the transportation task of the empty and heavy trailer, respectively. Constraint (11) represents the flow balance of the trailer at any node.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Xu et al [8] have established a model of tractor-and-trailer transportation for enterprises and designed specific transportation routes. He et al [9] considered the factors of carbon emissions from the perspective of environmental protection and studied the problem of inland container tractor-and-trailer transportation. With the deepening of research, Bian et al [10] considered the three forms of transportation routes of the complete vehicle, truck, and hybrid under the tractor-and-trailer transportation mode, built the model with the travel time as the objective function, and solved it using a two-stage hybrid heuristic algorithm.…”

Section: Introductionmentioning

confidence: 99%

Study on the Location-Routing Problem in Network-Type Tractor-and-Trailer Transportation Mode

Wang

Liu

et al. 2023

Sustainability

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Under the trend of developing green transportation in China, tractor-and-trailer transportation has received more attention. This paper focuses on the network-type tractor-and-trailer transportation mode in the port hinterland, aiming to tackle the problems of low efficiency and customer satisfaction in the existing transportation network. The authors recommend considering opening several alternative depots and making vehicle scheduling decisions simultaneous in order to optimize the existing transportation network. Therefore, this paper constructs a bi-level programming model with a generalized total cost minimization as the objective function. The solution to the original problem is divided into two stages: the location-allocation problem and vehicle scheduling; a two-stage hybrid heuristic algorithm is designed to solve the problem. Through the continuous iteration of the upper genetic algorithm and the lower hybrid particle swarm algorithm, the overall optimization of the problem is achieved. Finally, a specific example verifies the model and the algorithm’s effectiveness. The results show that the method proposed in this paper can significantly improve customer satisfaction and reduce transportation costs to a certain extent. It can also provide effective theoretical decision support for logistics enterprises to carry out tractor-and-trailer transportation business and develop green transportation.

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“…Misra et al [9] proposed a mixed time discretization method, combined with rolling time horizon, to solve the complicated multi-period inventory routing problem of marine empty and heavy containers. He et al [10] studied the scheduling method of tractor between port and inland hinterland, and constructed a mixed integer programming model with the goal of minimizing carbon emission costs. Chen et al [11] focused on the transportation mode for port collection of container trucks outside ports and proposed a method relied on vehicle time window to minimize the total cost of export containers.…”

Section: Introductionmentioning

confidence: 99%

Truck scheduling optimization for port collection and distribution based on multi-dimensional space-time network

Yang,

Zhang,

Zhang

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

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This paper studies the integrated optimization of two-way truck scheduling for import and export container collection and distribution of port and surrounding hinterland with time window constraints. A multi-dimensional time-space-state network was constructed based on the physical network to dynamically reflect the spatio-temporal trajectory and loading conditions of trucks. Aiming at maximizing the container volume of collection and distribution, minimizing the total transport cost and the amount of trucks dispatched, a multi-objective integer programming model was formulated to optimize the truck scheduling for port container collection and distribution based on service network. Taking the short distance import and export container collection and distribution in Shanghai Port of the Yangtze Delta as an example, the Gurobi9.5.2 was used to solve the optimization model. The results indicated that the multi-dimensional time-space-state network can rationally plan the truck routes and collecting and distributing process, thus achieving the integrated optimization of two-way truck scheduling for port container collection and distribution with time window constraints while dynamically reflecting the spatio-temporal trajectory and loading conditions of trucks. These inferences are expected to serve as a theoretical support for sustainable source of port collection and distribution.

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The Inland Container Transportation Problem with Separation Mode Considering Carbon Dioxide Emissions

Cited by 10 publications

References 49 publications

Modeling and Optimization of Container Drayage Problem with Empty Container Constraints across Multiple Inland Depots

Modeling and Optimization of Container Drayage Problem with Empty Container Constraints across Multiple Inland Depots

Study on the Location-Routing Problem in Network-Type Tractor-and-Trailer Transportation Mode

Truck scheduling optimization for port collection and distribution based on multi-dimensional space-time network

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