Laure Brisoux-Devendeville

Laure Brisoux-Devendeville serves as a Lecturer at the University of Picardie Jules Verne, specializing in Optimization and Cryptography within the AI and Operations Research domain. Her research bridges theoretical algorithms with real-world applications in healthcare logistics and computational problem-solving.

Her core research interests include:

• Combinatorial optimization for facility location (p-center problems with capacity constraints, stratification)
• Metaheuristic development (Ant Colony Optimization, Adaptive Large Neighborhood Search, Variable Neighborhood Search)
• Healthcare system optimization (training simulation scheduling, patient pathway planning)
• Logistics and transportation (pickup-and-delivery problems, parcel distribution)
• Constraint programming for conference scheduling and resource allocation

Analysis of her 15 most recent publications reveals a dominant focus on healthcare applications (47% of works), particularly using nature-inspired algorithms for training simulation centers and patient journey planning. Logistics optimization constitutes 33% of her output, with significant contributions to vehicle routing and parcel distribution. Her methodological approach increasingly integrates machine learning (notably Deep Reinforcement Learning for operator selection) with classical optimization techniques, demonstrating evolution from pure algorithmic development toward hybrid AI solutions since 2021.

Dr. Brisoux-Devendeville actively contributes to applied research through projects including:

• SMILE PICK UP (CIFRE industrial research partnership)
• Simusanté (health simulation training systems)
• LORH (logistics optimization research hub)