114 research outputs found

    A two-phase approach for periodic home health care planning

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    International audienceIn this paper, we study the problem of periodic vehicle routing encountered in Home Health Care (HHC). The problem can be considered as a Periodic Vehicle Routing Problem with Time Windows (PVRPTW). It consists in establishing a planning of visits to patients over a given time horizon so as to satisfy the adherence to the care plan while optimizing the routes used in each time period. One two-stage mathematical formulation of this problem is proposed. We then propose a Tabu Search (TS) and a MIP-based Neighborhood Search method to compute the weekly and daily plan, respectively. These approaches are tested on large size instances

    The City Logistics Facility Location Problem

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    National audienceThe aim of this work is to propose a new model that we call the City Logistics Facility Location Problem (CLFLP). Our purpose when introducing the CLFLP, is to capture essential aspects of distribution in cities, while maintaining a reasonable level of genericity and simplicity in the defintion of the problem. Practically, this model was adapted to the case of the city of Marseilles (France) and inserted into a Decision Support System. With a more academic point of view, the model could serve as a cornerstone for the development of new models and methods for strategic issues in city logistics

    A modeling approach for locating logistics platforms for fast parcels delivery in urban areas

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    International audienceThis study aims at defining a framework for optimizing, in a sustainable way (i.e. economical, eco-friendly and societal), the location of logistics platforms in urban areas. A first case study for our work is the city of Marseilles (France) which already has a logistics platform right in its centre (ARENC: 41362 m2 of warehouses and offices). In this abstract, we first provide a precise description of the problem we intend to solve. We then propose a mathematical model for representing it. Preliminary experimentations, based on the city of Marseilles, are then described; figures and preliminary results which are proposed for this first case study are obtained thanks to a decision-making software we have implemented. Conclusions and future works are finally drawn

    Online Large-Scale Taxi Assignment: Optimization and Learning

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    We propose a solution method for online vehicle routing, which integrates a machine learning routine to improve tours’ quality. Our optimization model is based on the Bertsimas et al. (2019) re-optimization approach. Two separate routines are developed. The first one uses a neural network to produce realistic pick-up times for the customers to serve. The second one relies on Q-learning in addition to random walks for the construction of the backbone graph corresponding to the instance problem of each time step. The second routine gives improved results compared to the original approach

    National survey of prevention and management of CMV infection in pediatric kidney transplantation in comparison to clinical practice guidelines

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    BackgroundCytomegalovirus (CMV) is one of the most frequent opportunistic infections in kidney transplant (KT) recipients and is a risk factor for patient and graft survival after KT. Center-to-center variation, optimal prevention and treatment strategies in pediatric KT are currently unknown. This survey aimed to assess current CMV prevention and treatment strategies used among French pediatric KT centers.MethodsA web-based survey was sent to all 13 French pediatric kidney transplantation centers.ResultsTwelve (92%) centers responded to the survey. All centers used prophylaxis for the donor-positive/recipient-negative (D+/R-) group. For R + patients, 54% used prophylaxis, 37% used a pre-emptive strategy. In the low-risk group, D-/R-, 50% used a pre-emptive approach and 50% had no specific prevention strategy. The antiviral used by all centers for prophylaxis was valganciclovir (VGCV). The duration of prophylaxis varied from 3 to 7 months and the duration of viral load monitoring varied from 6 months to indefinitely. No center used a hybrid/sequential approach. For the treatment of CMV DNAemia, VGCV or intravenous GCV were used. Therapeutic drug monitoring of VGCV was performed in 5 centers (42%). Five centers reported drug resistance. Eight centers (67%) administered VGCV during the treatment of acute graft rejection.ConclusionsThere is uniformity in CMV management in some areas among pediatric KT centers in France but not in others which remain diverse and are not up to date with current guidelines, suggesting unnecessary variation which could be reduced with better evidence to inform practice

    Pilotage Dynamique de Transport Sanitaire: Apprentissage et Optimisation

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    International audienceNous proposons deux méthodes de résolution pour le transport dynamique, i.e. arrivage des requêtes en temps réel, suivant une synergie entre apprentissage automatique et optimisation. La méthode d'optimisation de base est une ré-optimisation selon [Bertsimas et al., 2019]. La première amélioration utilise un réseau de neurones pour exploiter le contexte des instances à résoudre et produire des temps de ramassage de points réalistes. Tandis que la deuxième amélioration fait usage de l'apprentissage par renforcement en plus de marches aléatoire pour la construction du graphe support pour l'instance du problème correspondant à chaque pas de temps. Les benchmarks considérés dans le projet sont ceux de [Bertsimas et al., 2019] pour le transport urbain et de [Skiredj, 2021] pour le transport sanitaire
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