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Conception de services pour la mobilité urbaine respectueux des données privées et assurant la sécurité des clients et des véhicules

Abstract : This manuscript addresses the Dial-A-Ride Problem (DARP) using Private Vehicles and Alternative Nodes (DARP-PV-AN). The DARP consists of creating vehicle routes in order to ensure a set of users’ transportation requests. Each request corresponds to a client needing to be transported from his/her origin to his/her destination. Routing costs have to be minimized while respecting a set of constraints like time windows and maximum route length.In the classical DARP, vehicles have to start from a depot and come back to it at the end of their route. In the DARP-PV-AN, the on-demand transportation service can be done either by a public fleet or by clients that use their private vehicles. The use of these vehicles adds more flexibility and unclog the public transportation fleet by allowing clients to organize their own transportation. However, it also raises some privacy concerns. The DARP-PV-AN addresses these concerns and focuses on location privacy, i.e. the ability to prevent third parties from learning clients’ locations, by keeping both original and final location private. This is addressed by setting several pickup/delivery nodes for the transportation requests, thus masking the private address.The DARP-PV-AN is first solved in a mono-objective context. A compact mixed integer linear model is presented and an Evolutionary Local Search (ELS) is proposed to compute solutions of good quality for the problem. These methods are benchmarked on a modified set of benchmark instances. A new set of realistic instances is also provided to test the ELS in a more realistic way. A second approach solving the mono-objective DARP-PV-AN is proposed. Based on a hybrid metaheuristic, it combines three methods: a genetic algorithm, a Branch and Bound method, and Integer Linear Programming (ILP) to solve the Weighted Set Cover Problem (WSCP). This approach is tested on the new instances and compared to the previously proposed ELS.This hybrid method is then tuned to solve the DARP-PV-AN in a bi-objective context. In order to do this, the multi-objective algorithm NSGA-II is used, always associated with a Branch and Bound method and bi-objective WSCP solving by ILP (Integer Linear Programming). For the bi-objective WSCP resolution, different aggregation methods were tested and compared. This approach is also tested on the new instances, modified to treat them in a bi-objective framework.
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David Brevet. Conception de services pour la mobilité urbaine respectueux des données privées et assurant la sécurité des clients et des véhicules. Recherche opérationnelle [cs.RO]. Université Clermont Auvergne, 2019. Français. ⟨NNT : 2019CLFAC069⟩. ⟨tel-02530481⟩

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