Ouael Mouelhi
IMT Mines Alès, École Nationale Supérieure des Mines de Paris
Papers
3
Total Citations
10
H-Index
2
About
Ouael Mouelhi’s research lies at the intersection of artificial intelligence, multicriteria optimization, and mechatronic product design. His work focuses on developing intelligent computational methods to help designers navigate the complex, high-dimensional parameter spaces inherent in modern product development. Mouelhi’s core contribution is the creation of AI-driven frameworks—including hybrid search algorithms—that simultaneously optimize multiple, often conflicting, design objectives while respecting both technical specifications and customer needs. His most-cited paper, “An Artificial Intelligence approach for the multicriteria optimization in mechatronic products design” (2009, 5 citations), introduces a pioneering method for integrating AI into the design optimization process. This work, along with his studies on hybrid search algorithms and complex product evaluation (each garnering 2–3 citations), establishes a foundational approach for automating and improving decision-making in engineering design. By addressing the challenge of evaluating countless parameter combinations, Mouelhi’s research provides practical tools that enhance efficiency and innovation in mechatronics, making his contributions valuable for researchers and practitioners in design automation and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Multicriteria optimization and evaluation in complex products design2 citations · 2009