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About

Erlianasha Samsuria is a rising researcher in intelligent manufacturing and autonomous robotics, whose work focuses on optimizing production and navigation in flexible manufacturing systems (FMS). Her primary contributions lie in developing hybrid computational intelligence methods—specifically adaptive fuzzy-genetic algorithms—to solve complex scheduling problems involving mobile robots in job-shop environments. Her most cited paper (2024, 16 citations) introduces an adaptive fuzzy-genetic operator framework that significantly improves mobile robot scheduling efficiency, while a follow-up study (2025, 8 citations) enhances this approach with local search mechanisms for integrated production and robot scheduling. Samsuria also addresses the practical challenge of autonomous navigation in dynamic environments, proposing and evaluating algorithms for multi-robot coordination within laboratory-scale FMS setups. Her work bridges the gap between theoretical optimization and real-time industrial application, demonstrating how adaptive algorithms can handle uncertainty and changing conditions. With a growing citation record and a clear trajectory toward more robust, scalable solutions, Samsuria is establishing herself as a promising voice in the fields of manufacturing automation, swarm robotics, and intelligent scheduling.