Michel Gamache

Papers

Total Citations

H-Index

About

Michel Gamache is a researcher whose work sits at the dynamic intersection of operations research, artificial intelligence, and automated logistics systems. His primary focus centers on Robotic Mobile Fulfillment Systems (RMFSs) — cutting-edge automated warehouses that deploy fleets of small robots to retrieve and store shelves of items, increasingly central to modern e-commerce infrastructure. Gamache has made significant contributions to formalizing this emerging field, most notably through a comprehensive mathematical modelling framework for RMFSs that has garnered 37 citations since its 2021 publication, establishing itself as a foundational reference for researchers entering the space. Beyond mathematical formalization, he has pushed the boundaries of intelligent warehouse management by integrating machine learning approaches, exploring supervised learning combined with tree search methods for real-time storage allocation decisions, and applying reinforcement learning techniques to develop adaptive storage policies. This blend of classical optimization and modern AI reflects Gamache's forward-looking research philosophy. His body of work addresses a genuinely pressing industrial challenge — helping supply chains meet the demands of rapid, cost-effective e-commerce delivery — making his contributions relevant to both academic researchers and industry practitioners navigating the future of warehouse automation.