Hajar Nouinou

Hajar Nouinou is a Teacher-researcher at CESI Nancy Campus specializing in production scheduling, operational research, and optimization. She contributes to both academic teaching and research within the Engineering and Digital Tools research team, focusing on industrial engineering applications.

Her educational background includes:

• Doctorate from the University of Technology of Troyes (2021) on "Semi-online scheduling on unit machine for the industry of the future"
• Research Master's Degree in Industrial Systems Engineering from the University of Lorraine, Metz (2018)
• Engineering Diploma in Industrial Engineering and Logistics from the National School of Applied Sciences of Tangier (2018)

Her research centers on production scheduling and operational research, with emphasis on modeling and simulation of production systems. She integrates computer science and optimization techniques to develop algorithms for smart manufacturing environments, particularly addressing energy efficiency and renewable energy integration in scheduling problems. Her work bridges theoretical scheduling models with practical industrial applications in Industry 4.0 contexts.

Analysis of her 15 most recent publications reveals a dominant focus on semi-online scheduling algorithms for single-machine environments (60% of works), with growing emphasis on energy-aware scheduling (25%) and industry-specific applications like textile manufacturing (15%). Key trends include the integration of pricing decisions with production scheduling and the extension of scheduling models to incorporate renewable energy sources and storage systems.

She currently co-supervises two PhD candidates (J. Mhanna and R. Ben Chabane) with 2026 defenses and has guided multiple master's internships including D. El Khouni's 2024 work on remanufacturing pricing strategies. Her research is supported by projects addressing sustainable manufacturing and smart scheduling systems.

Nouinou operates within CESI Nancy's Engineering and Digital Tools research team, which develops computational methods for industrial engineering challenges, with current projects focusing on energy-flexible production scheduling and digital transformation in manufacturing.