Gradiente geotérmico (∆T)

This thesis is divided into 6 chapters, Chapters 1 and 6 are the thesis introduction and conclusion, respectively. The four main chapters, Chapters 2 to 5, are all written in the format of a scientific paper. Some have already been accepted for publication, and others have been submitted recently, where editorial decisions are expected in the next few months. This means that all chapters can be read in succession or independently.

For this reason, there are some repetitions in respect to the concepts as well as the background information throughout the document that cannot be avoided. Despite the independence between chapters, this thesis is not merely a collection of papers, since they form a logical evolution that is related. In Figure 1.1 the thesis flowchart is shown.

Figure 1.1 - Schematic figure of the thesis outline

Chapter 2 is the result of a comprehensive literature review of research articles and scientific reports that have been done on carsharing, mainly during the last years and until the publication date of the paper (Jorge and Correia, 2013). This chapter focuses specifically on: carsharing history and trends, carsharing demand modeling, and one-way carsharing systems modeling in terms of explaining the vehicle imbalance problem, its performance, and the ways of solving the vehicle imbalance problem. A primary focus is on the mathematical models developed so far with the objective of identifying

Chapter 1

principles for carsharing operators to manage these systems. It should be noted that since 2013, the publication date of the paper presented in this chapter, some new studies have appeared about carsharing that can help bridge the gaps previously identified. The new studies are referred to in chapters 3, 4, and 5.

Chapters 3 and 4 present ways of managing imbalance of vehicle stocks in one-way carsharing systems. The methodological approaches to address these issues are optimization (mathematical programming models) and simulation.

Chapter 3 introduces relocation operations of vehicles between stations using a staff of drivers as a way to solve vehicle imbalance issues. With this objective, two tools are developed: a mathematical programming model to optimize relocation operations that maximizes the profitability of the company; and a simulation model that allows testing different real-time relocation policies. The profitability combines the trips paid by customers, and the costs of running the system, such as: relocation, vehicle maintenance, vehicle depreciation, and station parking maintenance. In these models, all demand between existing stations must be satisfied. The real time relocation policies are based on historical data and some of them also use some of the results achieved with the optimization model as basis for obtaining better solutions. Both mathematical and simulation approach results are compared using trip data from the city of Lisbon (Portugal). The optimization results are the best ones possibly obtained, but simulated relocation policies are much more applicable in reality, because in the existing carsharing systems the travelers do not have to reserve their vehicles in advance.

formulate a mathematical programming model with the decision being to increase or decrease the price of travelling from an origin zone to a destination zone according to the vehicle stocks in the origin and destination zones. We consider that there is a negative price elasticity of demand, which allows changing demand for balancing vehicle stocks. In this model, the goal is again to maximize the profitability of a carsharing company considering the revenues obtained through the trips paid by clients, and the costs of vehicle maintenance, vehicle depreciation, and station maintenance.

Given the dependence between demand and price, the model is non-linear, which leads to the need of creating a solution algorithm to solve it. Therefore, a meta-heuristic is developed for solving the problem. As in Chapter 3, the model was applied to the case-study of Lisbon (Portugal).

To the best of our knowledge, Chapter 5 introduces, for the first time, the integration of both round-trip and one-way carsharing. The objective of this chapter is to study if a round-trip carsharing system is able to be profitable by allowing one-way trips for specific origin-destination pairs, considering that the round-trip service already exists and for this reason should be served in priority. An integer programming model is developed to decide which one-way trips to/from a major trip generator should be allowed in a round-trip service in order to maximize the profit of the company. This profit is computed taking into consideration the revenues that are obtained through the trips paid by the clients, and the costs that correspond to maintenance of the vehicles used for the one-way service, high demand generator station parking, and vehicle

model: the number of parking spaces in each existing round-trip station is not increased;

and the fleet of vehicles is limited to the number of vehicles currently existing in the round-trip service. This model was applied to the case study of the Logan Airport in Boston, United States of America, considering that one-way trips are allowed from the existing Zipcar stations in the city (Zipcar(b), 2014) to the Airport and vice-versa.

Finally, Chapter 6 summarizes the work developed throughout this thesis and presents the main conclusions withdrawn from it.