Stage M2 - Planification de production avec contenants de transport réutilisables - Université Paris Saclay

OFFRE DE STAGE NIVEAU M2 A L'UNIVERSITE PARIS SACLAY

Optimizing industrial production planning with returnable transport items

Keywords : production planning, lot-sizing, circular economy, mixed-integer linear programming

Context

Industrial supply chains rely heavily on transport packaging such as crates, boxes, pallets, and container to facilitate product handling, transportation, and storage. While single-use packaging is common, its disposal after delivery depletes natural resources and generates substantial waste. 

To mitigate these environmental impacts, many firms are transitioning toward Returnable Transport Items (RTIs). Designed for durability and repeated use, RTIs enable a circular flow: once delivery is completed, the packaging is returned to the point of origin (e.g., a manufacturing facility or distribution centre) for cleaning, refurbishment, and reuse.

RTI-based systems can significantly enhance supply chain sustainability, with the potential to reduce CO2​ emissions by 60-80% and packaging waste by over 90%. However, realizing these benefits depends critically on achieving a sufficient number of reuse cycles and ensuring that reverse logistics (i.e., the backward transportation, cleaning, and refurbishment of RTIs) is efficiently coordinated with production and distribution activities.

The primary challenge here lies in the tight coupling and circular dependency between production and transportation plans, and the availability of RTIs, as a shortage of empty RTIs at the manufacturing facility can impact production, transportation, and on-time satisfaction of the customer demand. 

 Internship

The objective of this internship is to develop advanced optimization models and algorithms, grounded in Operations Research, to address these complexities. Specifically, we propose to investigate a mathematical programming approach to jointly optimize the short-term planning of production, distribution, and RTI circulation in a supply chain. 

The core scientific challenge lies in developing a mathematical programming model that is sufficiently detailed to yield practically relevant operational plans, while designing an efficient solution algorithm capable of providing near-optimal solutions within a computational timeframe compatible with industrial requirements.

Candidate profile

We are seeking a candidate currently enrolled in a Master’s degree or the final year of an engineering curriculum, with a specialization in:

• Operations Research
• Combinatorial Optimization
• Computer Science
• Industrial Engineering
• or a related discipline.

Requirements:

• Proficiency in the formalization of complex optimization problems via mathematical programming (Linear Programming, Mixed-Integer Linear Programming)
• Good programming skills (Python, C++)
• Proficiency in English for reviewing scientific literature and communicating findings

Practical information

Supervision: The internship will be jointly supervised by Céline Gicquel (Associate Professor at the University Paris Saclay) and Melek Rodoplu (Associate Professor at the University d’Evry)

Environment: The internship will take place at the Laboratoire Interdisciplinaire des Sciences du Numérique (LISN) of the Université Paris Saclay.

Laboratoire Interdisciplinaire des Sciences du Numérique
Campus d’Orsay – building 660 
5 rue René Thom
91190 Gif-sur-Yvette

Time and duration: The start of the internship is flexible but should be in Spring 2027. The expected duration is 4 to 6 months.

Contact: Candidates must send their CV, a letter of motivation and, if available, their academic transcript to Céline Gicquel (celine.gicquel@lisn.fr) and Melek Rodoplu (melek.rodoplu@univ-evry.fr).