Dr Mohammad Humyun Fuad Rahman

Dr. Mohammad Humyun Fuad RAHMAN is a Research Associate at the Capability Systems Centre, the University of New South Wales, Canberra. His research lies in the area of Manufacturing System optimization considering uncertainty and disruptions, Industry 4.0, Project and Supply Chain management. Dr. Rahman obtained his PhD from the School of Engineering and IT, University of New South Wales (2011-2015), where he worked on the topic of modelling reactive scheduling problems in real-time Flow shop production environments and solving them by efficient heuristic and meta-heuristic algorithms.

He was a Post-Doctoral Fellow at the Department of Mechanical and Manufacturing Engineering, Aalborg University, Denmark from 2017 to 2018. During his Postdoctoral Fellowship he developed reliable and efficient decision support systems for scheduling/rescheduling systems of Unmanned Autonomous Vehicle (UAV) fleets considering real-life constraints and the project was funded by AirBus Defence and Space. Beside this, he engaged in supervising students’ projects for solving planning and scheduling problems from Danfoss and LEGO, and was able to help them in problem identification and providing solutions to improve their existing production systems. He is also collaborating with other researchers from different countries in manufacturing optimization.

He has experienced in teaching and supervising in undergraduate and postgraduate levels in Australia and Denmark in the area of production planning and control, project and supply chain management, heuristic and meta-heuristic algorithms, and inventory management.

Journal articles

Rahman HF; Sarker R; Essam D, 2018, 'Multiple-order permutation flow shop scheduling under process interruptions', International Journal of Advanced Manufacturing Technology, vol. 97, pp. 2781 - 2808, http://dx.doi.org/10.1007/s00170-018-2146-z

Rahman HF; Sarker R; Essam D, 2017, 'A genetic algorithm for permutation flowshop scheduling under practical make-to-order production system', Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, vol. 31, pp. 87 - 103, http://dx.doi.org/10.1017/S0890060416000196

Rahman HF; Sarker R; Essam D, 2015, 'A real-time order acceptance and scheduling approach for permutation flow shop problems', European Journal of Operational Research, vol. 247, pp. 488 - 503, http://dx.doi.org/10.1016/j.ejor.2015.06.018

Rahman HF; Sarker R; Essam D, 2015, 'A genetic algorithm for permutation flow shop scheduling under make to stock production system', Computers and Industrial Engineering, vol. 90, pp. 12 - 24, http://dx.doi.org/10.1016/j.cie.2015.08.006

Rahman HF; Sarker R; Essam D, 2014, 'A real-time order acceptance and scheduling approach for permutation flow shop problems', European Journal of Operational Research, http://dx.doi.org/10.1016/j.ejor.2015.06.018

Conference Papers

Rahman HF; Sarker RA; Essam DL; Chang G, 2014, 'A memetic algorithm for solving permutation flow shop problems with known and unknown machine breakdowns', in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014, pp. 42 - 49, presented at , http://dx.doi.org/10.1109/CEC.2014.6900242

Rahman HF; Sarker RA; Essam DL, 2013, 'A memetic algorithm for Permutation Flow Shop Problems', in 2013 IEEE Congress on Evolutionary Computation, CEC 2013, pp. 1618 - 1625, presented at , http://dx.doi.org/10.1109/CEC.2013.6557755

Rahman H; Sarker R; Essam D, 2013, 'Permutation Flow Shop Scheduling with dynamic job order arrival', in Proceedings of the 2013 IEEE Conference on Cybernetics and Intelligent Systems, CIS 2013, pp. 30 - 35, presented at , http://dx.doi.org/10.1109/ICCIS.2013.6751574