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Publications
Socially Assistive Robots for patients with Alzheimer's Disease: A scoping review.
Substitution of dietary monounsaturated fatty acids from olive oil for saturated fatty acids from lard increases LDL apolipoprotein B-100 fractional catabolic rate in subjects with dyslipidemia associated with insulin resistance: a randomized controlled trial.
Substitution of dietary monounsaturated fatty acids from olive oil for saturated fatty acids from lard increases LDL apolipoprotein B-100 fractional catabolic rate in subjects with dyslipidemia associated with insulin resistance: a randomized controlled trial.
Substitution of dietary monounsaturated fatty acids from olive oil for saturated fatty acids from lard increases low-density lipoprotein apolipoprotein B-100 fractional catabolic rate in subjects with dyslipidemia associated with insulin resistance: a randomized controlled trial
The « jingle-jangle fallacy » of empathy: Delineating affective, cognitive and motor components of empathy from behavioral synchrony using a virtual agent
Efficiently solving a vehicle routing problem (VRP) in a practical runtime is a critical challenge for delivery management companies. This p… (voir plus)aper explores both a theoretical and experimental connection between the Capacitated Vehicle Routing Problem (CVRP) and the Constrained Centroid-Based Clustering (CCBC). Reducing a CVRP to a CCBC is a synonym for a transition from an exponential to a polynomial complexity using commonly known algorithms for clustering, i.e K-means. At the beginning, we conduct an exploratory analysis to highlight the existence of such a relationship between the two problems through illustrative small-size examples and simultaneously deduce some mathematically-related formulations and properties. On a second level, the paper proposes a CCBC based approach endowed with some enhancements. The proposed framework consists of three stages. At the first step, a constrained centroid-based clustering algorithm generates feasible clusters of customers. This methodology incorporates three enhancement tools to achieve near-optimal clusters, namely: a multi-start procedure for initial centroids, a customer assignment metric, and a self-adjustment mechanism for choosing the number of clusters. At the second step, a traveling salesman problem (T SP) solver is used to optimize the order of customers within each cluster. Finally, we introduce a process relying on routes cutting and relinking procedure, which calls upon solving a linear and integer programming model to further improve the obtained routes. This step is inspired by the ruin&recreate algorithm. This approach is an extension of the classical cluster-first, route-second method and provides near-optimal solutions on well-known benchmark instances in terms of solution quality and computational runtime, offering a milestone in solving VRP.
