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Guillaume Dalle (EPFL)06/10/2023 13:30
The Julia graphs ecosystem has emerged as a worthy competitor to alternatives in other languages (eg. Python's networkx), promising to combine ease of use with scalability. Unfortunately, it contains a large number of packages with very different purposes, and navigating them can be tricky at first. In this tutorial, I will provide an overview of the ecosystem, highlighting the general...
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Louis Bouvier (Ecole des Ponts)06/10/2023 14:00
This talk highlights the fruit of a partnership with Renault. Their return logistic requires solving a continent-scale multi-attribute inventory routing problem (IRP). It corresponds to the following situation: a supplier manages the delivery of several commodities to its customers on a multiple-day horizon in a centralized manner. The supplier has to plan routes to deliver commodities from...
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Alireza Shefaei (TU Delft)06/10/2023 14:30
We present a JuMP-based solver that combines a nested primal-dual decomposition technique and convex relaxation approaches for tackling non-convex multi-stage stochastic programming problems. The approach addresses optimal long-term water supply infrastructure planning with constraints feasibility at operational timescales. We combine an outer primal decomposition of planning stages and inner...
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Emanuele Natale (UCA)06/10/2023 15:30
In the network alignment problem, we are given two graphs and we are asked to match their respective vertices in order to minimize some similarity measure. The problem implies as a special case the fundamental problem of subgraph isomorphism, and arises in several applications, from computer vision to the analysis of protein-protein interaction networks. In this talk, we will give an overview...
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Vincent Le Chenadec (Gustave Eiffel Université)06/10/2023 16:00
We present a recently developed Julia implementation of the Domain Decomposition Method (DDM). DDM is a powerful framework for formulating preconditioning techniques. The objectives of our package are twofold: (1) to implement DDM primitives for easy prototyping of new preconditioning strategies and (2) to leverage them to solve the linear systems that arise from Computational Fluid Dynamics...
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