A Novel Data-Driven Approach for Solving the Electric Vehicle Charging Station Location-Routing Problem

Hung, Ying; Michailidis, George

doi:10.1109/tits.2022.3196835

Cited by 9 publications

(7 citation statements)

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“…To reduce the difficulty of solving, another approach is to decompose the complex ELRP problem into several sub-problems to be solved separately, i.e., the ELRP can be divided into the EFLP [29] and EVRP [30]. The EFLP is one of the sub-problems in the ELRP and is to decide the optimal location in the network, especially the electric charging stations [2,3,[15][16][17] or the battery swapping stations [12,29]. In the EVRP, a single vehicle is required to achieve the maximum profit and minimum cost with constraints that the route duration is not more than a given threshold.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Electric vehicles (EVs) are widely popular worldwide due to their support for environmental sustainability, which can greatly reduce fossil fuel consumption and pollutant emissions. However, the construction and investment of charging facilities can also cause damage to environmental sustainability, so the electric location-routing problem (ELRP) is of great significance for promotion of EVs and environmental sustainability [1,2]. The ELRP is composed of two sub-problems: the electric facility location problem (EFLP) [3] and the electric vehicle (EV) routing problem (EVRP) [4].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, researchers generally believe that the ELRP problem is a more complex task than a traditional location-routing problem (LRP). And the application of the ELRP will become increasingly widespread with the popularity of electric vehicles, such as charging station locations [2,11], battery swapping stations [12], smart cities [6], urban logistics [9,13], home health care [12], waste collection [14], electric trucks [7], electric aircraft [15], and electric buses [16].…”

Section: Introductionmentioning

confidence: 99%

“…Hence, the ELRP can be considered as a combination of the knapsack problem and the traveling salesman problem (TSP) [18,19]. The TSP is an ancient LRP to maximize the total objective function of different routes limited by time duration, but the ELRP has to consider power consumption [6,9] and the layout of charging facilities while optimizing TSP, considering elements such as the charging station location [2,11], and battery swapping station location [12]. Therefore, the ELRP is an NP-hard problem where no polynomial-time algorithms can be used to effectively solve it, and the traditionally exact solution algorithms may be very time-consuming and not suitable for practical applications.…”

Section: Introductionmentioning

confidence: 99%

“…Although it is better to optimize the network planning of the ELRP from the beginning, the benchmark tests for the ELRP are also rare. Due to the increasing attention paid to the ELRP in recent years [1,2,46,47], the main motivation of our work is to develop a more efficient solving mechanism for the ELRP. To the best of our knowledge, this is the first work to use an artificial P. polycephalum colony to address the ELRP from the viewpoint of network planning, and we also develop a benchmark test for the ELRP from the viewpoint of charging network planning.…”

mentioning

confidence: 99%

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An Artificial Physarum polycephalum Colony for the Electric Location-Routing Problem

Cai,

Wang,

et al. 2023

Sustainability

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Electric vehicles invented for environmental sustainability are prone to adverse impacts on environmental sustainability due to the location and construction of their charging facilities. In this article, an artificial Physarum polycephalum colony is proposed to solve the novel challenging problem. First, the electric location-routing problem is established as a multi-objective network panning model with electric constraints to provide the optimal charging infrastructure layout, electric vehicle maintenance costs, and traffic conditions. The electric facility location problem and vehicle routing problem are integrated by integer programming, which considers the total distance, total time, total cost, total number of electric vehicles, and order fill rate. Second, an artificial Physarum polycephalum colony is introduced to solve the complex electric location-routing problem and includes the two basic operations of expansion and contraction. In the expansion operation, the optimal parent individuals will generate more offspring individuals, so as to expand the population size. In the contraction operation, only individuals with high fitness will be selected to survive through a merge sorting algorithm, resulting in a decrease in population size to the initial value. Through the iterative computing of the two main operations, the proposed artificial Physarum polycephalum colony can finally find the optimal solution to the objective function. Third, a benchmark test is designed for the electric location-routing problem by extracting the real road network from Tokyo, and the experimental results prove the effectiveness and applicability of this work.

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