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Dr A. Ghasemi (Amir)

Senior lecturer and researcher
Telephone:
0643406241
Email:
a.ghasemi2@hva.nl
Work address:
Fraijlemaborg, Fraijlemaborg 133, 1102 CV Amsterdam
Postal address:
Postbus 524,1000 AM Amsterdam
Social media:
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Dr. Amir Ghasemi joined the Amsterdam School of International Business (AMSIB) in 2021 as a senior lecturer and researcher in International Supply Chain Management at the Department of IT Logistics after a Postdoctoral study in CONFIRM Centre for Smart Manufacturing in Ireland. He obtained his PhD degree in Industrial Engineering and Operations Management from University of Limerick, School of Engineering, under supervision of Prof. Cathal Heavey in 2021. His Research mainly focuses on designing simulation, optimization, and Machine Learning (ML)-based Decision Support Tools for transforming Business Process Models and Value Chains towards the implementation of Digitalization, Sustainability, and Circular Economy within both service and manufacturing industries. He has published articles within the peer reviewed flagship journals such as Applied Soft Computing, Journal of Manufacturing Systems, and Engineering Optimization in addition to being an active member of the Winter Simulation Conference community.

He is currently engaged with the REFLOW Project working with Prof. Lori Divito aiming to develop circular and regenerative cities through enabling active citizen involvement and systemic change to re-think the current approach to material flows in cities. His main role is to design a Digital Twin (DT) for the Circular Garment Supply Chain Network between hospitals, manufacturers, and service providers.

At AMSIB, Dr. Ghasemi teaches courses on International Supply Chain Management and Data Analytics. He used to be a member of Productive 4.0 project (2017 to 2020) focusing on creating a user platform across value chains and industries and promoting the digital networking of manufacturing companies, production machines and products within EU mainly cooperating with semiconductor manufacturers such as Robert Bosch GmbH and Infineon Technologies AG.

  • Optimizing Portfolio Selection Strategy for Purchasing and Supply in Healthcare Considering Circular Economy Principles - Case: Isolation Gowns
    Ghasemi, A., DiVito, L., Ingen-Housz, Z., & Torabi, S. A. (2023). Optimizing Portfolio Selection Strategy for Purchasing and Supply in Healthcare Considering Circular Economy Principles - Case: Isolation Gowns. SSRN - Elsevier. https://doi.org/10.2139/ssrn.4320927
  • Demonstration of the Feasibility of Real Time Application of Machine Learning to Production Scheduling
    Ghasemi, A., Kabak, K. E., & Heavey, C. (2022). Demonstration of the Feasibility of Real Time Application of Machine Learning to Production Scheduling. In B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C. G. Corlu, L. H. Lee, E. P. Chew, T. Roeder, & P. Lendermann (Eds.), Proceedings of the 2022 Winter Simulation Conference, WSC 2022 (pp. 3406-3417). (Proceedings - Winter Simulation Conference; Vol. 2022-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC57314.2022.10015436
  • Evolutionary Learning Based Simulation Optimization for Stochastic Job Shop Scheduling Problems
    Ghasemi, A., Ashoori, A., & Heavey, C. (2021). Evolutionary Learning Based Simulation Optimization for Stochastic Job Shop Scheduling Problems. Applied Soft Computing, 106, 1-19. [107309]. https://doi.org/10.1016/j.asoc.2021.107309
  • Proposing a lower bound for a nonlinear scheduling problem in supply chain
    Beheshtinia, M. A., & Ghasemi, A. (2021). Proposing a lower bound for a nonlinear scheduling problem in supply chain. International Journal of Nonlinear Analysis and Applications, 12(1), 1073-1085. https://doi.org/10.22075/IJNAA.2017.1616.1422
  • An Evaluation of Strategies for Job Mix Selection in Job Shop Production Environments-Case: A Photolithography Workstation
    Ghasemi, A., & Heavey, C. (2021). An Evaluation of Strategies for Job Mix Selection in Job Shop Production Environments-Case: A Photolithography Workstation. In S. Kim, B. Feng, K. Smith, S. Masoud, Z. Zheng, C. Szabo, & M. Loper (Eds.), 2021 Winter Simulation Conference (WSC) (Proceedings - Winter Simulation Conference; Vol. 2021-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC52266.2021.9715478
  • Optimizing capacity allocation in semiconductor manufacturing photolithography area – Case study
    Ghasemi, A., Azzouz, R., Laipple, G., Kabak, K. E., & Heavey, C. (2020). Optimizing capacity allocation in semiconductor manufacturing photolithography area – Case study: Robert Bosch. Journal of Manufacturing Systems, 54, 123-137. https://doi.org/10.1016/j.jmsy.2019.11.012
  • A review of simulation-optimization methods with applications to semiconductor operational problems
    Ghasemi, A., Heavey, C., & Laipple, G. (2019). A review of simulation-optimization methods with applications to semiconductor operational problems. In WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause (pp. 3672-3683). [8632486] (Proceedings - Winter Simulation Conference; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2018.8632486
  • Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area
    Ghasemi, A., Heavey, C., & Kabak, K. E. (2019). Implementing a new genetic algorithm to solve the capacity allocation problem in the photolithography area. In WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause (pp. 3696-3707). [8632204] (Proceedings - Winter Simulation Conference; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2018.8632204
  • A multi-objective and integrated model for supply chain scheduling optimization in a multi-site manufacturing system
    Beheshtinia, M. A., & Ghasemi, A. (2018). A multi-objective and integrated model for supply chain scheduling optimization in a multi-site manufacturing system. Engineering Optimization, 50(9), 1415-1433. https://doi.org/10.1080/0305215X.2017.1400546
  • Supply chain scheduling and routing in multi-site manufacturing system (case study
    Beheshtinia, M. A., Ghasemi, A., & Farokhnia, M. (2018). Supply chain scheduling and routing in multi-site manufacturing system (case study: a drug manufacturing company). Journal of Modelling in Management, 13(1), 27-49. https://doi.org/10.1108/JM2-10-2016-0094
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