Publications

2025

1. Integrating Aggregated Electric Vehicle Flexibilities in Unit Commitment Models using Submodular Optimization

   Hélène Arvis, Olivier Beaude, Nicolas Gast, Stéphane Gaubert, and Bruno Gaujal

   Nov 2025

   Abs arXiv

   The Unit Commitment (UC) problem consists in controlling a large fleet of heterogeneous electricity production units in order to minimize the total production cost while satisfying consumer demand. Electric Vehicles (EVs) are used as a source of flexibility and are often aggregated for problem tractability. We develop a new approach to integrate EV flexibilities in the UC problem and exploit the generalized polymatroid structure of aggregated flexibilities of a large population of users to develop an exact optimization algorithm, combining a cutting-plane approach and submodular optimization. We show in particular that the UC can be solved exactly in a time which scales linearly, up to a logarithmic factor, in the number of EV users when each production unit is subject to convex constraints. We illustrate our approach by solving a real instance of a long-term UC problem, combining open-source data of the European grid (European Resource Adequacy Assessment project) and data originating from a survey of user behavior of the French EV fleet.

2023

1. Mixed-Integer Programming and State-of-the-Art Heuristic Approaches for the Scheduling of Modular Automotive Body-in-White Production

   Jan Markus Gelfgren, Hélène Arvis, Simon Hagemann, and Sigrid Wenzel

   In Production Processes and Product Evolution in the Age of Disruption, Nov 2023

   Series Title: Lecture Notes in Mechanical Engineering

   Abs DOI

   Conventional, linear assembly lines cannot meet the flexibility requirements imposed by the automotive market development. The concept of modular production has the potential to solve these challenges. However, there is no applicable solution for scheduling modular body-in-white (BIW) production systems. This paper addresses this research gap and presents adaptions of a mixed-integer programming (MIP) model and of the two heuristic approaches Late Acceptance Hill Climbing (LAHC) and Particle Swarm Optimisation (PSO) for scheduling of modular BIW production systems. Thus, the presented approaches capture the characteristics of BIW production systems in more detail than comparable approaches in literature. Subsequently, the approaches are compared for different modular BIW production scenarios. The comparison suggests that a MIP approach with a PSO starting solution provides the best makespans. However, the relative performance of the scheduling approaches can depend on the production layout.

2. Mixed-Integer Programming Model for Scheduling of Modular Automotive Body-In-White Production Systems

   Jan M. Gelgfren, Hélène Arvis, Simon Hagemann, and Sigrid Wenzel

   In Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains, Nov 2023

   Series Title: ARENA2036

   Abs DOI

   Abstract The turbulent transition in the automotive industry towards electric vehicles is highly challenging, both in product development and in production. Conventional, linear assembly lines struggle to meet the flexibility requirements imposed by this market development. This paper presents the first mixed-integer programming (MIP) model which is tailor-made for the scheduling of modular body-in-white (BIW) production systems. The main novelty of the presented approach lies in using precedence graphs for modelling the joining steps of the BIW production and allowing for different capabilities at each workstation of the production system. Thus, the presented approach captures the characteristics of BIW production systems in more detail than comparable models available in the literature. The application of the presented approach to an exemplary production scenario with five jobs and 22 operations underlines the strengths of the proposed model but also indicates potential for future improvements.