Cyril Fonlupt

Université du littoral côte d'opale, Laboratoire d’Informatique Signal et Image de la Côte d’Opale

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About

Cyril Fonlupt is a leading researcher in swarm intelligence and metaheuristic optimization, with a particular focus on developing compact, computationally efficient algorithms. His most significant contribution is the creation of compact firefly algorithms, which address the high computational cost and memory demands of traditional population-based swarm methods. His seminal 2017 paper, "A set of new compact firefly algorithms," has garnered 56 citations, establishing a new direction for resource-constrained optimization. Fonlupt further refined this approach in his 2019 work on compact firefly optimisation techniques, demonstrating how probabilistic representation can drastically reduce algorithm footprint while maintaining search efficacy. Beyond firefly algorithms, he has advanced the field through innovative applications, including intelligent trajectory planning for humanoid robots using an elitism-based Selfish Gene Algorithm, and the development of a rate learning-based fish school search algorithm for global optimization. His work bridges the gap between theoretical algorithm design and practical deployment in robotics and complex systems, making swarm intelligence viable for embedded and real-time applications where memory and processing power are limited.