Journées Julia et Optimisation

Session

Julia & Graphs

Oct 6, 2023, 1:30 PM

Jean-Baptiste Say (CNAM Paris)

4. Tutorial on graphs in Julia

Guillaume Dalle (EPFL)

10/6/23, 1:30 PM

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...

1. Algorithm for the packaging return logistics at Renault: a Julia code in production

Louis Bouvier (Ecole des Ponts)

10/6/23, 2:00 PM

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...

10. Nested approaches for multi-stage stochastic planning problems

Alireza Shefaei (TU Delft)

10/6/23, 2:30 PM

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...

8. Algorithms for the network alignment problem

Emanuele Natale (UCA)

10/6/23, 3:30 PM

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...

7. A Julia implementation of the Domain Decomposition Method (DDM.jl)

Vincent Le Chenadec (Gustave Eiffel Université)

10/6/23, 4:00 PM

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...