Patrice Bonhomme
Papers
1
Total Citations
11
H-Index
1
About
Patrice Bonhomme is a leading figure in discrete event systems, with a primary focus on the modeling, analysis, and control of Petri nets. His most impactful work tackles the challenging problem of Minimum Initial Marking (MIM) estimation in Labeled Petri Nets (L-PN)—a critical task for system diagnosis and reconfiguration when only partial observations are available. In his highly cited 2020 paper, Bonhomme pioneered a novel approach inspired by the GRASP (Greedy Randomized Adaptive Search Procedure) metaheuristic, enabling efficient computation of possible initial markings from observed label sequences. This work, which has garnered 11 citations, bridges combinatorial optimization with formal methods, offering scalable solutions for complex industrial systems. Bonhomme’s contributions are particularly valued in manufacturing, robotics, and automated verification, where his algorithms provide robust tools for fault detection and system recovery. His research continues to influence the development of intelligent, self-adaptive control systems, making him a key reference for students and engineers working at the intersection of operations research and control theory.
Research Focus
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Top Papers
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