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The Thesis aims to develop a biobjective vehicle routing problem integrating costs and emissions into the optimization of routes with a heterogenouse fleet of vehicles.
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The dial a ride problem (DARP) is a specific transportation problem. The objective is to optimise the planning of a collection of trips made by a fleet of vehicles. Those trips aim to satisfy requests from users while meeting various constraints. The cleared example is the transportation of the elderly or disabled people. The problem has received increase interest in recent years as the demand for services that can be solved through DARP is rising. Due to the aging of the population, this demand will be even bigger in the future. Good optimisation tools are needed to respond to it. In this thesis, I review the different heuristics to solve DARP before implementing a hybrid Bee Algorithm with Deterministic Annealing. The different creation steps are described before the algorithm is tested on several instances. The results are then used to explore possible improvements to the algorithm. Several real-life problems are discussed along the way
Vehicle routing problem --- Dial a ride problem --- Optimisation --- Hybrid metaheuristic --- Bee algorithm --- Deterministic Annealing --- Sciences économiques & de gestion > Production, distribution & gestion de la chaîne logistique --- Ingénierie, informatique & technologie > Sciences informatiques
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