Adel Nikfarjam
Higher Degree by Research Candidate
School of Computer Science
Faculty of Sciences, Engineering and Technology
I received my bachelor and master degrees in Industrial Engineering from Azad University in 2011 and 2017, respectively. Currently, I am a PhD candidate at the optimisation research group of the school of computer science at the University of Adelaide.
My research interests mostly include the applications of Operations Research, Particularly in logistics as well as evolutionary computation.
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Journals
Year Citation 2021 Nikfarjam, A., & Moosavi, A. (2021). An integrated (1, T) inventory policy and vehicle routing problem under uncertainty: an accelerated Benders decomposition algorithm. Transportation Letters, 13(2), 104-124.
Scopus1 WoS22019 Moosavi, A., & Nikfarjam, A. (2019). A multi-path routing-inventory problem for a closed-loop supply chain considering the heterogeneous fleet of vehicles. International Journal of Sustainable Engineering, 12(3), 174-188.
Scopus22019 Rezaei, N., Ebrahimnejad, S., Moosavi, A., & Nikfarjam, A. (2019). A green vehicle routing problem with time windows considering the heterogeneous fleet of vehicles: Two metaheuristic algorithms. European Journal of Industrial Engineering, 13(4), 507-535.
Scopus9 WoS10 -
Conference Papers
Year Citation 2021 Nikfarjam, A., Bossek, J., Neumann, A., & Neumann, F. (2021). Entropy-based evolutionary diversity optimisation for the traveling salesperson problem. In F. Chicano, & K. Krawiec (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'21) (pp. 600-608). New York, NY: Association for Computing Machinery.
Scopus12021 Nikfarjam, A., Bossek, J., Neumann, A., & Neumann, F. (2021). Computing diverse sets of high quality TSP tours by EAX-based evolutionary diversity optimisation. In S. Finck, M. Hellwig, & P. S. Oliveto (Eds.), Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (pp. 9:1). ACM.
2017 Nikfarjam, A., Tayebi, H., & Ebrahimnejad, S. (2017). Applying an ordering policy in a two echelon inventory system to eliminate the uncertainty of poisson demand in the upstream level. In Proceedings of International Conference on Computers and Industrial Engineering, CIE.
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