Jayanta Kumar Debnath

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About

Jayanta Kumar Debnath is a researcher specializing in intelligent transportation systems, automation, and real-time optimization for urban infrastructure. His work focuses on the design and performance evaluation of automated parking management systems, particularly multi-story, robotic parking structures. Debnath’s major contributions include developing simulation-based scheduling algorithms that minimize customer wait times while maximizing spatial and operational efficiency in fully-automated parking facilities. His most-cited paper, "Design and performance evaluation of a parking management system for automated, multi-story and robotic parking structure" (2019, 22 citations), presents a comprehensive PMS design validated through simulation. Another key study, "Real-Time Optimal Scheduling of a Group of Elevators in a Multi-Story Robotic Fully-Automated Parking Structure" (2015, 11 citations), introduces a real-time scheduling algorithm for elevator systems that transport vehicles between floors, addressing critical bottlenecks in high-density parking environments. Debnath’s research has direct implications for smart city development, reducing urban congestion and improving user experience in automated facilities. His work is notable for bridging theoretical optimization with practical, scalable solutions, making him a valuable contributor to the fields of logistics, robotics, and intelligent infrastructure.