Arindam Majumder
Jadavpur University, Tripura University, National Institute of Technology Agartala
Papers
5
Total Citations
107
H-Index
4
About
Dr. Arindam Majumder is a leading researcher in industrial robotics and manufacturing optimization, with a focus on developing nature-inspired algorithms to solve complex scheduling and path planning problems. His work primarily addresses robotic cell scheduling with sequence-dependent setup times, where he has pioneered the application of swarm intelligence techniques. Majumder’s most influential contribution is his 2016 paper introducing a novel cuckoo search algorithm for two-machine robotic cell scheduling, which has garnered 44 citations and established a new benchmark in the field. He has also advanced bacterial foraging optimization algorithms for similar scheduling challenges, with his 2019 work receiving 28 citations. More recently, Majumder has applied teaching–learning-based optimization to multi-robot plant inspection systems (24 citations) and developed the hybrid A*-VG algorithm for inspection robot path planning (2023). His research demonstrates a consistent ability to adapt metaheuristic algorithms to real-world manufacturing constraints, achieving significant improvements in efficiency and task allocation. With over 100 total citations, Majumder’s work bridges theoretical optimization and practical industrial applications, making him a key figure in the evolution of intelligent robotic systems for modern manufacturing environments.
Research Focus
Key Achievements
Top Papers
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