Facility Location Selection for Ammunition Depots based on GIS and Pythagorean Fuzzy WASPAS

Authors

DOI:

https://doi.org/10.31181/jopi2120247

Keywords:

Pythagorean Fuzzy Sets, WASPAS, GIS, Ammunition, Recycling, Facility Location Selection

Abstract

The purpose of this study is to determine depot locations where expired ammunition will be controlled before being sent to recycling facilities. Expiration of ammunition means that using, transporting and even storing that ammunition where it is located poses a greater risk. For this reason, it is important to determine facility locations so that ammunition is stored in places that will least harm the environment and human health. The criteria to be used for ammunition depot location selection were determined through literature review, various researches and expert opinions. The proposed model is based on the combined use of Geographic information system (GIS) and multi-criteria decision making. For an example application of the model, a generic study on a district basis in Turkey is presented. Candidate depot locations were determined using GIS with the help of 6 main criteria and 18 sub-criteria. Then, candidate depot locations were ranked by the Pythagorean Fuzzy Set-based WASPAS (Weighted Aggregated Sum Product Assessing) method, taking into account the opinions of military experts for the main criteria. WASPAS method selected location A1 as the most suitable ammunition depot location. The results show that the proposed methodology can be practically applied.

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Author Biographies

  • Hakan Ayhan Dağıstanlı, Department of Industrial and System Engineering, Turkish Military Academy, National Defense University, Ankara, Turkiye

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  • Kemal Gürol Kurtay, Department of Industrial and System Engineering, Turkish Military Academy, National Defense University, Ankara, Turkiye

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Published

2024-01-10

How to Cite

Dağıstanlı, H. A., & Kurtay, K. G. . (2024). Facility Location Selection for Ammunition Depots based on GIS and Pythagorean Fuzzy WASPAS. Journal of Operations Intelligence, 2(1), 36-49. https://doi.org/10.31181/jopi2120247