Electric Vehicle Routing Problem with Heterogeneous Vehicles and Partial Charge

Park, Hyungbin; Jin, Sukho

doi:10.24867/ijiem-2020-4-266

Cited by 9 publications

(5 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, this study distinguishes itself from the existing literature by integrating the EVRP with multiple charging options and nonlinear charging functions. [23] CPLEX -Lee (2021) [29] Exact * Karakatič (2021) [30] Heuristic -Sayarshad and Mahmoodian (2021) [34] Exact -Lam et al (2022) [20] Exact * Cataldo-Díaz et al (2022) [21] Gurobi * Jiang et al (2022) [24] Heuristic 0.12 Akbay et al (2023) [25] Heuristic * Amiri et al (2023) [27] Heuristic -This study Heuristic 0.61…”

Section: Related Literaturementioning

confidence: 88%

“…They focused on decisions regarding charging methods and volumes in addition to determining electric vehicle routes. Park et al [23] adopted partial charging in an EVRP with heterogeneous vehicles, and developed a mathematical formulation to minimize the total distance traveled by the vehicles. Jiang et al [24] considered partial charging for a multi-depot e-bus scheduling problem with vehicle relocation constraints.…”

Section: Related Literaturementioning

confidence: 99%

See 1 more Smart Citation

The Routing Problem for Electric Truck with Partial Nonlinear Charging and Battery Swapping

Han,

Chen,

Fang

et al. 2023

Sustainability

View full text Add to dashboard Cite

The maritime industry has introduced the concept of “green ports” as a means to achieve sustainable development by reducing carbon emissions. Within ports, trucks play a crucial role in transportation operations. However, there is limited comprehensive research on the electric truck routing problem containing practical constraints such as charging options and charging processes. This study presents a more realistic routing problem for electric trucks, with a specific focus on multiple charging options within green ports. To address this challenge, we formulate a mixed-integer programming model designed to minimize overall operational costs associated with the transportation of trucks over the planning horizon. In order to solve this problem effectively, we devise an Adaptive Large Neighborhood Search (ALNS) algorithm, embedded with several customized operators. Through a series of numerical experiments, the effectiveness of the proposed algorithm is verified. The experimental results provide compelling evidence of the superior performance of the proposed algorithm compared to the original ALNS algorithm. Furthermore, sensitivity analysis is conducted, leading to valuable managerial insights.

show abstract

Section: Related Literaturementioning

confidence: 88%

Section: Related Literaturementioning

confidence: 99%

The Routing Problem for Electric Truck with Partial Nonlinear Charging and Battery Swapping

Han,

Chen,

Fang

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…(12) (13) Parameter denotes the position of a particle and indicates the speed of the particle on the k th iteration. Also, Pbest and Gbest represent the best solutions found by a particle and globally, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Various vehicle routing problems have been developed to cope with different situations, such as vehicle routing problems with time window constraints [1], heterogeneous fleet vehicle routing problems [2], the heterogeneous fixed fleet in an open vehicle routing problem [3], vehicle routing problem with multidepots [4,5,6]. Other excellent research related to different topics, including multi-compartment [7,8], pickup and delivery [9,10,11], feeder VRP [12], and electric VRP [13], can also be found in the literature. In addition to the conventional deterministic routing problems, some concentrated on solving the VRP with stochastic demand, such as vehicle routing problems with stochastic demand and duration constraints [14] and inventory routing problems with demand uncertainty [15].…”

Section: Introductionmentioning

confidence: 99%

A new hybrid algorithm for solving the vehicle routing problem with route balancing

Huang¹,

Huang²,

Lee³

et al. 2023

Int J Ind Eng Manag

View full text Add to dashboard Cite

This paper addresses a vehicle routing problem with route balancing to minimize the total travel cost and equity measurement. We propose a hybrid method combining Particle Swarm Optimization and Ant Colony Optimization with the global search characteristic of PSO and the path-finding ability of ACO. The proposed method first solves the benchmark instances to obtain the total travel distance and the equity measurement value. Then, by considering predefined threshold values of the equity measurement in the original solution, the vehicle routing problem with route balancing can be solved using the proposed method. Experiments are conducted to obtain better-balanced routes by considering more than one equity measurement. The results showed that this hybrid mechanism is promising to become a better method of VRP.

show abstract

“…The proposed solutions are then enhanced by using a large neighborhood search (LNS) algorithm. Park and Jin [136] model and apply an E-VRP with heterogeneous vehicles and partial charge. They consider different characteristics of vehicles, such as loading capacities, battery capacities, energy consumption rates, and charging speeds.…”

Section: E-vrps Focusing On Battery Rechargementioning

confidence: 99%

Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

et al. 2021

View full text Add to dashboard Cite

The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.

show abstract

Electric Vehicle Routing Problem with Heterogeneous Vehicles and Partial Charge

Cited by 9 publications

References 21 publications

The Routing Problem for Electric Truck with Partial Nonlinear Charging and Battery Swapping

The Routing Problem for Electric Truck with Partial Nonlinear Charging and Battery Swapping

A new hybrid algorithm for solving the vehicle routing problem with route balancing

Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

Contact Info

Product

Resources

About