Researcher

Mr Farhad Habibi

Keywords

optimisation

project management

operations research & management science

resilience modelling

Fields of Research (FoR)

Logistics and Supply Chain Management, Operations Research, Optimisation

Biography

Farhad Habibi is currently doing his PhD in project management at the University of New South Wales, Canberra, Australia. He achieved his master's degree in Industrial Engineering (Systems Optimization) from the Iran University of Science and Technology in 2017. He focuses on mathematical modelling and optimization techniques in supply chain and scheduling problems. His research interests mainly include multi-objective optimization,...view more

Farhad Habibi is currently doing his PhD in project management at the University of New South Wales, Canberra, Australia. He achieved his master's degree in Industrial Engineering (Systems Optimization) from the Iran University of Science and Technology in 2017. He focuses on mathematical modelling and optimization techniques in supply chain and scheduling problems. His research interests mainly include multi-objective optimization, optimization under uncertainty, supply chain resilience, decision-making in transportation systems, sustainable design, and project scheduling. His PhD research area is related to Designing Resilient Supply Chain Model: Application of AI and Prescriptive Analytics. The readers are referred to the provided link for further information about this subject.
He is also a Research Associate at Decision Support and Analytics Research Group, University of New South Wales (UNSW Canberra), where he is working on optimizing supply chain embedded project scheduling problems.

My Research Activities

Habibi, F., Chakrabortty, R. K., & Abbasi, A. (2023). Maximizing projects’ profitability, environmental score, and quality: a multi-project scheduling and material ordering problem. Environmental Science and Pollution Research, 1-38.
Habibi, F. (2022). A survey on Australian supply chains during the COVID-19 pandemic and key resilience strategies. Journal of Future Sustainability, 2(4), 145-148.
Habibi, F., Abbasi, A., & Chakrabortty, R. K. (2022). Designing an efficient vaccine supply chain network using a two-phase optimization approach: a case study of COVID-19 vaccine. International Journal of Systems Science: Operations & Logistics, 1-34.
Habibi, F., Barzinpour, F., & Sadjadi, S. J. (2019). A mathematical model for project scheduling and material ordering problem with sustainability considerations: A case study in Iran. Computers & industrial engineering, 128, 690-710.
Habibi, F., Asadi, E., & Sadjadi, S. J. (2018). A location-inventory-routing optimization model for cost effective design of microalgae biofuel distribution system: A case study in Iran. Energy strategy reviews, 22, 82-93.
Asadi, E., Habibi, F., Nickel, S., & Sahebi, H. (2018). A bi-objective stochastic location-inventory-routing model for microalgae-based biofuel supply chain. Applied energy, 228, 2235-2261.
Habibi, F., Barzinpour, F., & Sadjadi, S. (2018). Resource-constrained project scheduling problem: review of past and recent developments. Journal of project management, 3(2), 55-88.
Habibi, F., Birgani, O., Koppelaar, H., & Radenović, S. (2018). Using fuzzy logic to improve the project time and cost estimation based on Project Evaluation and Review Technique (PERT). Journal of Project Management, 3(4), 183-196.
Habibi, F., Barzinpour, F., & Sadjadi, S. J. (2017). A multi-objective optimization model for project scheduling with time-varying resource requirements and capacities. Journal of industrial and systems engineering, 10(special issue on scheduling), 92-118.
Habibi, F., Asadi, E., Sadjadi, S. J., & Barzinpour, F. (2017). A multi-objective robust optimization model for site-selection and capacity allocation of municipal solid waste facilities: A case study in Tehran. Journal of cleaner production, 166, 816-834.
Habibi, F., Asadi, E., & Sadjadi, S. (2017). Developing a location-inventory-routing model using METRIC approach in inventory policy. Uncertain Supply Chain Management, 5(4), 337-358.