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Identifying the Influential Factors in Increasing the Efficiency of Network Systems: A Mixed Binary Linear Programming

Author

Listed:
  • Reza Feizabadi

    (Hakim Sabzevari University)

  • Mehri Bagherian

    (University of Guilan)

Abstract

Old models in data envelopment analysis (DEA) consider decision-making units (DMUs) as black boxes. Therefore, they do not have a proper efficiency to evaluate network systems. This shortcoming has led to the emergence of network models that take the performance of a system’s processes into account in calculating the performance, and some of which also assign a certain value of performance to the processes. However, no model has examined the effect of intermediate factors in a network system, while the study of these intermediate factors can greatly help to increase the efficiency of a system. In this paper, our aim is to present a mixed binary linear programming that identifies the intermediate factors that are relatively more effective in increasing the performance of a network system. At the end, the new model is implemented on a small network system in order to better describe the performance, as well as on a real-world network system.

Suggested Citation

  • Reza Feizabadi & Mehri Bagherian, 2023. "Identifying the Influential Factors in Increasing the Efficiency of Network Systems: A Mixed Binary Linear Programming," SN Operations Research Forum, Springer, vol. 4(4), pages 1-14, December.
    • Handle: RePEc:spr:snopef:v:4:y:2023:i:4:d:10.1007_s43069-023-00259-8
    DOI: 10.1007/s43069-023-00259-8
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    References listed on IDEAS

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