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Algoriths for optimizing shared mobility systems

Abstract : Bikes sharing systems have known a growing success all over the world. Several attempts have been made since the 1960s. The latest developments in ICT have enabled the system to become efficient. People can obtain real-time information about the position of the vehicles. More than 200 cities have already introduced the system and this trend keeps on with the launching of the NYC system in spring 2013. A new avatar of these means of transportation has arrived with the introduction of Autolib in Paris end of 2011. The objective of this thesis is to propose algorithms that may help to improve this system efficiency. Indeed, operating these systems induces several issues, one of which is the regula tion problem. Regulation should ensures users that a right number of vehicles are present at any station anytime in order to fulfill the demand for both vehicles and parking racks. This regulation is often executed thanks to trucks that are travelling the city. This regulation issue is crucial since empty and full stations increase users' dissatisfaction. Finding the optimal strategy for regulating a network appears to be a difficult question. This thesis is divided into two parts. The first one deals with the "static" case. In this part, users' impact on the network is neglected. This is the case at night or when the system is closed. The operator faces a given repartition of the vehicles. He wants the repartition to match a target one that is known a priori. The one-truck and multiple-truck balancing problems are addressed in this thesis. For each one, an algorithm is proposed and tested on several instances. To deal with the "dynamic" case in which users interact with the system, a simulator has been developed. It is used to compare several strategies and to monitor redistribution by using trucks. Strategies not using trucks, but incentive policies are also tested: regularly updated prices are attached to stations to deter users from parking their vehicle at specified stations. At last, the question to find the best initial inventory is also addressed. It corresponds to the case when no truck are used within the day. Two local searches are presented and both aim at minimizing the total time lost by users in the system. The results obtained can be used as inputs for the target repartitions used in the first part.
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Daniel Chemla. Algoriths for optimizing shared mobility systems. Operations Research [cs.RO]. Ecole nationale des ponts et chaussées - ENPC PARIS / MARNE LA VALLEE, 2012. English. ⟨pastel-00837006⟩

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