A Fuzzy Logic Transportation Model for Optimizing Pharmaceutical Supply Chain in Iran

Authors

  • Ferial Zarrabi Caspian Faculty of Engineering, College of Engineering, University of Tehran, Tehran, Iran.
  • Seyed Omid Hasanpour Jesri * Caspian Faculty of Engineering, College of Engineering, University of Tehran, Tehran, Iran.

https://doi.org/10.48314/anowa.v1i3.49

Abstract

The pharmaceutical industry in Iran plays a significant role in the nation’s economy. This sector's supply chain is made up of various players, including suppliers of chemicals and packaging materials, as well as retailers who market these products. The structure of this supply chain is quite extensive, encompassing production facilities, storage units, distributors, and wholesalers such as pharmacies, hospitals, and government purchasing centers, along with retailers spread across different regions. This research introduces a transportation strategy specifically for the pharmaceutical industry, with the goal of streamlining logistics operations. The proposed framework takes into account a variety of elements, decision-making variables, and constraints, reflecting the complex dynamics of drug supply networks. To evaluate how well the transportation model performs under uncertain conditions, fuzzy logic techniques are employed. The primary objective is to enhance operational efficiency, lower costs, and improve the overall effectiveness of logistics within the pharmaceutical sector. The results demonstrate the viability and success of the proposed approach in addressing the challenges related to managing transportation in the pharmaceutical field.

Keywords:

Pharmaceutical supply chain, Optimization, Transportation model, Fuzzy method, Iran pharmaceutical industry

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Published

2025-09-27

Issue

Vol. 1 No. 3 (2025): Annals of Optimization With Applications (ANOWA)

Section

Articles

How to Cite

Zarrabi , F. ., & Hasanpour Jesri, S. O. . (2025). A Fuzzy Logic Transportation Model for Optimizing Pharmaceutical Supply Chain in Iran. Annals of Optimization With Applications, 1(3), 182-191. https://doi.org/10.48314/anowa.v1i3.49

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