Laboratoire de Génie Informatique et d’Automatique de l’Artois

Open position (Ph.D. student)

Sustainable fishery supply chain design in the context of a circular economy

Temporary (3 years) Beginning: 01/09/2023

The aim of this project is to adopt a transdisciplinary approach by focusing in particular on the supply chain of seafood products and its optimization in the context of a circular economy and strong human pressures exerted on marine ecosystems.

Keywords: Fishery, sustainable supply chain design, circular economy, optimisation

Important

​Ph.D. thesis grant starting at fall 2023:

  • Sumission applications are due for May 31st, 2023
  • The PhD grant funding will only be guaranteed after validation of the subject/applicant pair by the jury.

Context

This part is only in french.

  • Laboratoire(s) d’accueil du consortium IFSEA : LGI2A-Laboratoire de Génie Informatique et d’Automatique de l’Artois (Université d’Artois)
  • Équipe : Optimisation des systèmes complexes (Optisco)
  • Spécialité : Optimisation de la chaîne logistique durable
  • Directeur/Directrice de thèse et établissement de rattachement : Pr. Hamid ALLAOUI (Université d’Artois) - hamid.allaoui@univ-artois.fr
  • Co-Directeur/Co-Directrice de thèse et établissement de rattachement : Pr. Frida LASRAM (ULCO), LOG-Laboratoire d’Océanologie et de Géosciences (Université du Littoral Côte d’Opale) - frida.lasram@univ-littoral.fr
  • Projet : Cette bourse est proposée dans le cadre du lancement de l’Ecole Universitaire de Recherche IFSEA (Transdisciplinary graduate school for marIne, Fisheries and SEAfood sciences). Cette EUR, lancée en 2022, a pour objectif de relever les défis environnementaux, sociétaux et économiques de la filière des produits de la mer.
  • Financement : 50% Université d’Artois, 50% IFSEA

Thesis topic

Title of the thesis: Sustainable fishery supply chain design in the context of a circular economy

Abstract

The aim of this project is to adopt a transdisciplinary approach by focusing in particular on the supply chain of seafood products and its optimization in the context of a circular economy and strong human pressures exerted on marine ecosystems.

This study aims to optimize the energy, environmental and economic costs of the supply chain of seafood products from the source to the end customer. It requires the construction of a spatialized location model of supply sources (fishing and/or aquatic sector), mass storage and sorting, transformation, and distribution to take into account environmental constraints and establish a cost-distance matrix for optimization. logistics.

This involves designing, verifying and optimizing the logistics network of the virtuous loop between the various actors. We thus want to globally estimate the economic, social and environmental impact of a set of alternative scenarios that the decision-maker can define or that we can propose to him. Optimal solutions for one of these criteria or situations of compromise between several criteria will be studied within the framework of this project. The transport part is here at the heart of this logistics network that we seek to optimize.

The methodology that will be used for the location of the layers of the logistics network will require the integration of methods from Artificial Intelligence (AI) and Operational Research (OR).

References

  • Hamid ALLAOUI — Yuhan GUO — Alok CHOUDHARY — Jacqueline BLOEMHOF. Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach, Computers & Operations Research, COR, pp 369-384, Vol. 89, 01/2018
  • Yuhan GUO — Youssef BOULAKSIL — Hamid ALLAOUI — Fangxia HU, Solving the sustainable supply chain network design problem by the multi-neighborhoods descent traversal algorithm. Computers and Industrial Engineering, CAIE, pp 107098, Vol. 154, 04/2021
  • Hamid ALLAOUI — Yuhan GUO — Joseph SARKIS, Decision support for collaboration planning in sustainable supply chains. Journal of Cleaner Production, JCP, pp 761-774, Vol. 229, 12/2019, 2019 Revue Internationale avec Comité de Lecture
  • Nicolas DANLOUP — Hamid ALLAOUI — Gilles GONCALVES, A comparison of two meta-heuristics for the pickup and delivery problem with transshipment. Computers & Operations Research, COR, pp 155-171, Vol. 100, Elsevier, 12/2018

Candidacy

Skills

  • Master or Engineering degree in Computer Science, Operations Research, Applied Mathematics
  • Knowledge of Logistics concepts
  • Optimization , Machine Learning and Programming Python, C/C++, Java

How to apply

Please send a CV, a covering letter, your scores and ranking during the last two years of academic studies, and a letter(s) of recommendation to all the following persons:

  • hamid.allaoui@univ-artois.fr
  • frida.lasram@univ-littoral.fr
  • issam.nouaouri@univ-artois.fr

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