Relocation optimization of electric cars in one-way car-sharing systems: modeling,exact solving and heuristics algorithms

Car-sharing system with electric cars is a very convenient service for urban transportation: it allows users to pick up a vehicle at a station and rent it during a short time. To manage this kind of system in the best way, it is necessary to solve the critical problem of vehicle stock imbalance across the stations. Several decision levels must be considered to balance the car distribution by taking into account the quality of service and the system operation cost. To this end, a linear programming model is proposed to formalize the problem in a mathematical framework, which allows the computation of optimal vehicle distribution strategies. To make our solution time efficient and usable for solving large problems, a greedy algorithm and a tabu search algorithm are proposed. These two algorithms are applied to the Auto Bleue network in Nice and its surrounding (France) using extensive simulations. Besides, an integrated mapping method is provided within the Geographical Information System QGIS to estimate flows and their locations. Numerical results demonstrate that the tabu search algorithm is able to find near-optimal solutions and good compromises between client satisfaction, number of staff agents and vehicles used, and computing time.     

Personalized sightseeing tours: a model for visits in art museums

This article describes a method to provide adapted visit tours in art museums according to the preferences expressed by the visitor and exhibits prestige. It is based on a dual approach with, on the one hand an automatic textual analysis of the official information available online (labels of exhibits) that allows to rank the exhibit attractiveness for a standard museum visitor. On the other hand, individual preferences are also taken into account to adapt the visit according to the personal cultural awareness of the visitor. We use operations research to solve a routing optimization problem, aiming at finding a visit tour with time constraints and maximization of the visitor satisfaction. Depending on the instance size and the problem scale, an integer linear programming (ILP) model and a greedy algorithm are proposed to recommend personalized visit tours and applied on two museums: ‘Musée de l’Orangerie’ in Paris and ‘National Gallery’ in London. The obtained results show that it is possible to recommend a good tour to visitors of an art museum by taking into account the common prestige of the exhibits and the individual interests, joining automatic text summarization and routing optimization in a limited geographical space.     

Initiating collective action for the management of deep confined aquifer systems: application of a participatory scenario approach in France

Hydrogeology Journal - Large deep confined aquifer systems play a crucial role for water and food security and the economic development of rural areas. However, there are few cases, worldwide, of...     

Synthetic stellar and SSP libraries as templates for Gaia simulations

ESA’s Gaia mission will collect low resolution spectroscopy in the optical range for ～10⁹ objects. Complete and up-to-date libraries of synthetic stellar spectra are needed to built algorithms aimed to automatically derive the classification and the parametrization of this huge amount of data. In addition, libraries of stellar spectra are one of the main ingredients of stellar population synthesis models, aiming to derive the properties of unresolved stellar populations from their integrated light. We present (a) the newly computed libraries of synthetic spectra built by the Gaia community, covering the whole optical range (300–1100 nm) at medium-high resolution of (0.3 nm) for stars spanning the most different types, from M to O, from A-peculiar to Emission lines to White Dwarfs, and (b) the implementation of those libraries in our SSP code (Tantalo in The Initial Mass Function 50 Years Later, 327:235 2005), exploring different stellar evolution models.     

Fluctuation theory of ambient noise imaging

Travel time estimation and reflector imaging can be carried out using the cross correlations of signals generated by ambient noise sources and recorded at sensor arrays. We study here the mean and variance of the estimated quantities both with respect to the distribution of the noise sources and with respect to the distribution of the randomly scattering medium. In particular, we discuss the trade-off between resolution enhancement due to illumination diversification by scattering and the associated signal-to-noise ratio reduction, also due to scattering.