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Selective and co-modal transport : models and algorithms

Abstract : The notion of "co-modality" was introduced by the European Commission in 2006 as part of its new transport policy. It refers to the "efficient use of different modes on their own and in combination" for the purpose of achieving "an optimal and sustainable utilisation of resources" [55]. Unlike previous European transport policies, co-modality does not seek to oppose road transportation to its alternatives, but rather seeks to take advantage of the domains of relevance of different transportation modes and of their combinations to optimize services. In this thesis, we focus on developing new solution algorithms for variants of vehicle routing problems for city logistics systems arising in the wake of comodality. We were particularly interested in developing effective solution methods for selective variants of the vehicle routing problem and two-echelon variants. First, we address the Team Orienteering Problem with Time Windows (TOPTW), a selective variant of routing problems that takes into account customer availability. We propose an effective algorithm based on a neighborhood search that alternates between two different search spaces, and uses a long term memory mechanism to benefit from information gathered while exploring the search space, to solve the TOPTW. In the se cond part of this work, we deal with the Two-Echelon Vehicle Routing Problem (2E-VRP), a variant of the problem that introduces intermediate facilities, refered to as « satellites ». In a two echelon system, freight is first moved from the depot to the satellites using large trucks, and then delivered from the satellites to the customers using smaller vehicles. To solve the 2E-VRP, we introduce a novel algorithm that combines heuristic methods with mathematical programming techniques. Finally, we consider the Orienteering Problem with Hotel Selection (OPHS), another selective variant that shares similarities with the 2E-VRP, namely, the use of intermediate facilities called hotels. For this problem, we propose a new integer linear programming model, valid inequalities and a Branch-&-Cut solution method. Extensive experimentation on benchmark instances available in the literature demonstrate the competitiveness of our solution methods.
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Youcef Amarouche. Selective and co-modal transport : models and algorithms. Other [cs.OH]. Université de Technologie de Compiègne, 2019. English. ⟨NNT : 2019COMP2522⟩. ⟨tel-02884343⟩

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