@article { ,
	title = {A multi-objective approach to infrastructure planning in the early stages of EV introduction},
	editor = {F.-Javier Heredia; Cristina Corchero},
	year = {2014},
	month = {27/01/2014},
	type = {MSc Thesis},
	address = {Faculty of Mathematics and Statistics},
	abstract = {This study approaches the problem from the perspective of a central planner wishing to install fast charging stations. A multi-objective approach is used to simultaneously consider two conflicting objectives in the optimisation problem. The first objective is to minimise the distance that potential consumers would need to deviate from their normal journeys in order to reach their nearest fast charging station, and thus minimise the associated inconvenience. The second objective is to minimise the set up costs associated with the installation of the stations, which differ according to the number of facilities installed and their location. These objectives are normalised using a function transformation and then combined into a single objective function. A mathematical model is formulated and implemented using GAMS to obtain results for the case study of Barcelona, building on the existing literature. Using the weighted sums method, multiple Pareto optimal solutions are found by solving for different relative weights combinations applied to the two objectives. These solutions are used to depict the Pareto front, offering insight into the nature of the trade-offs between the objectives and aiding the decision making process. This study develops the existing methodology used for the EV infrastructure problem, and shows how the application of a multi-objective formulation can offer useful insight to decision makers, particularly when preferences are unclear a priori.},
	keywords = {Multi-objective Optimisation; Facility Location; Electric Vehicle; Fast Charging Stations; MSc Thesis},
	URL = {http://hdl.handle.net/2099.1/20851},
	author = {Andina Rosalia Brown}
}

