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Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers

Research output: Thesis › Master's Thesis

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Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers. / Krishnan, Advaith.
Lancaster University, 2023. 55 p.

Research output: Thesis › Master's Thesis

Harvard

Krishnan, A 2023, 'Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers', Masters by Research, Lancaster University. https://doi.org/10.17635/lancaster/thesis/2118

APA

Krishnan, A. (2023). Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers. [Master's Thesis, Lancaster University]. Lancaster University. https://doi.org/10.17635/lancaster/thesis/2118

Vancouver

Krishnan A. Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers. Lancaster University, 2023. 55 p. doi: 10.17635/lancaster/thesis/2118

Author

Krishnan, Advaith. / Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers. Lancaster University, 2023. 55 p.

Bibtex

@mastersthesis{16ea0edee2cf4c3ab30e7cd209872b8b,
title = "Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers",
abstract = "This thesis proposes a unique Vehicle Routing Problem (VRP) focusing on charging management optimisations for electric vehicles with prioritised customers. This problem is modelled as a hybrid of the Travelling Repairman Problem (TRP) and the Electric Vehicle Routing Problem (EVRP). After a brief literature review around the scope of the problem, a base mathematical model is formulated to explain the constraints and objective function of the problem. The problem is solved using a Nearest Neighbour Based Heuristic (NNBH) and Simulated Annealing with Variable Neighbourhood Search. The Nearest Neighbour Based Heuristic (NNBH) generates an initial solution. The initial solution is used by the metaheuristic for achieving a better final solution. The base mathematical model is used to benchmark the performance ofthe solution approach. The algorithmic framework developed is run for smaller and larger instances to demonstrate the accuracy and scalability of the model produced, respectively. The computational results of both instances show the success of the proposed model.",
keywords = "Electric Vehicles (EVs), Mathematical Optimisation, Simulated Annealing, Variable Neighborhood Search, vehicle routing problem, prioritisation, Fleet Planning, electric vehicle charger",
author = "Advaith Krishnan",
year = "2023",
month = aug,
day = "30",
doi = "10.17635/lancaster/thesis/2118",
language = "English",
publisher = "Lancaster University",
school = "Lancaster University",

}

RIS

TY - GEN

T1 - Charging Constrained Electric Vehicle Routing Problem with Prioritized Customers

AU - Krishnan, Advaith

PY - 2023/8/30

Y1 - 2023/8/30

N2 - This thesis proposes a unique Vehicle Routing Problem (VRP) focusing on charging management optimisations for electric vehicles with prioritised customers. This problem is modelled as a hybrid of the Travelling Repairman Problem (TRP) and the Electric Vehicle Routing Problem (EVRP). After a brief literature review around the scope of the problem, a base mathematical model is formulated to explain the constraints and objective function of the problem. The problem is solved using a Nearest Neighbour Based Heuristic (NNBH) and Simulated Annealing with Variable Neighbourhood Search. The Nearest Neighbour Based Heuristic (NNBH) generates an initial solution. The initial solution is used by the metaheuristic for achieving a better final solution. The base mathematical model is used to benchmark the performance ofthe solution approach. The algorithmic framework developed is run for smaller and larger instances to demonstrate the accuracy and scalability of the model produced, respectively. The computational results of both instances show the success of the proposed model.

AB - This thesis proposes a unique Vehicle Routing Problem (VRP) focusing on charging management optimisations for electric vehicles with prioritised customers. This problem is modelled as a hybrid of the Travelling Repairman Problem (TRP) and the Electric Vehicle Routing Problem (EVRP). After a brief literature review around the scope of the problem, a base mathematical model is formulated to explain the constraints and objective function of the problem. The problem is solved using a Nearest Neighbour Based Heuristic (NNBH) and Simulated Annealing with Variable Neighbourhood Search. The Nearest Neighbour Based Heuristic (NNBH) generates an initial solution. The initial solution is used by the metaheuristic for achieving a better final solution. The base mathematical model is used to benchmark the performance ofthe solution approach. The algorithmic framework developed is run for smaller and larger instances to demonstrate the accuracy and scalability of the model produced, respectively. The computational results of both instances show the success of the proposed model.

KW - Electric Vehicles (EVs)

KW - Mathematical Optimisation

KW - Simulated Annealing

KW - Variable Neighborhood Search

KW - vehicle routing problem

KW - prioritisation

KW - Fleet Planning

KW - electric vehicle charger

U2 - 10.17635/lancaster/thesis/2118

DO - 10.17635/lancaster/thesis/2118

M3 - Master's Thesis

PB - Lancaster University

ER -