Juillet, 2021

02jul14 h 00 min16 h 00 minSoutenance de thèse Victor Hugo CANTU MEDRANO

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Détails

Thèse intitulée : Metaheuristic and matheuristic approaches for multi-objective optimization problems in process engineering: application to the hydrogen supply chain design

Vendredi 2 juillet à 14h00 dans la Amphi 100 de l’ENSIACET

Lien Zoom :
https://univ-tlse3-fr.zoom.us/j/81602765826?pwd=dEdOdGQrdklkTGV3V3dxTEZITDRjdz09
ID de réunion : 816 0276 5826
Code secret : 491889

Le lien sera actif aux alentours de 13h30, merci de bien vouloir garder micros et caméras coupés

Composition du jury :

  • M Antonio ESPUÑA, Professeur, Universitat Politècnica de Catalunya (rapporteur)
  • M Jean-Baptiste CAILLAU, Professeur, Université Côte d’Azur (rapporteur)
  • M Bruno SARENI, Professeur, INP-ENSEEIHT LAPLACE (examinateur)
  • M José María PONCE ORTEGA, Professeur, Universidad Michoacana de San Nicolás de Hidalgo (examinateur)
  • Mme Annabelle BRISSE, Docteure, European Institute for Energy Research (examinatrice)
  • Mme Catherine AZZARO-PANTEL, Professseure, INP-ENSIACET-LGC (directrice de thèse)
  • M Antonin PONSICH, Professeur associé,   Universidad Autónoma Metropolitana,  Azcapotzalco, México (directeur de thèse)

Du fait du contexte sanitaire, le traditionnel pot de thèse ne pourra malheureusement pas avoir lieu.

Résumé de la thèse :
Complex optimization problems are ubiquitous in process systems engineering (PSE). Multiobjective evolutionary algorithms (MOEAs) constitute potential alternatives to classical optimization methods. Nevertheless, their performance strongly depends on the technique employed for handling constraints. The objective of this work is to explore the applicability of recent advances in Evolutionary Computation to complex optimization problems, to present alternative solution methods to the PSE community.
A first part of the research was devoted to the study of constraint-handling techniques within metaheuristics. The obtained results obtained on test functions indicated the superiority of the technique using the constraint gradient to repair infeasible solutions.
The second part of the thesis is devoted to the optimal design of sustainable hydrogen supply chains (HSCs), considering both economic and environmental criteria. This complex problem present features that entail difficulties to both classical and metaheuristic techniques.
A hybrid technique (matheuristic) developed in this purpose demonstrated its efficacy for generating an approximation of the Pareto front. Besides, this approach allowed considering a more realistic representation of the HSC, accounting for technological, spatial and temporal aspects of its design.

Mots clés : Multiobjective evolutionary algorithms, constraint-handling techniques, hydrogen supply chains, bilevel optimization, matheuristic.

Date et heure

(Friday) 14 h 00 min - 16 h 00 min

Location

Amphi 100 INP-ENSIACET

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