Applying the Learning WASPAS Technique to Determine the Optimal Green Route in the Distribution of Dairy Products (Case Study: Kaleh Company)

Document Type : Original Article

Authors

1 PhD Student, Industrial Engineering, No.C., Islamic Azad University, Noor, Iran. Email: a.fazlollahniaomran@iau.ac.ir

2 Corresponding Author, Assistant Professor, Department of Industrial Engineering, No.C., Islamic Azad University, Noor, Iran. Email: fa.harsej@iau.ac.ir

3 Assistant Professor, Department of Computer, No.C., Islamic Azad University, Noor, Iran. Email: knms81@gmail.com

4 Assistant Professor, Department of Mathematics and Statistics, No.C., Islamic Azad University, Noor, Iran. Email: r_rezaeyan@iaunour.ac.ir

Abstract

In today's world, choosing the optimal route for distributing dairy products is recognized as a major challenge in the supply chain. The present study aims to systematically review the weighted sum product evaluation method as well as the step-by-step weighted evaluation tool to present an improved learning model. This paper seeks to determine a green route for dairy products to reduce both cost and time of sending goods, while also minimizing the environmental impacts associated with dairy product transportation in Kaleh Company's distribution system in Amol City. To achieve this goal, the WASPAS multi-criteria decision-making method, with a very high accuracy, has been used to select the optimal route. For this purpose, by proposing the VASPAS learning method, this study seeks to correct the weaknesses in the computational methods. The presented model is able to identify and evaluate the optimal routes using machine learning algorithms and multi-criteria analyses. The results of implementing the proposed method for distributing dairy products in the cities of Mazandaran province indicate a significant increase in accuracy in identifying the optimal route and, consequently, a reduction in cost, time, and environmental impacts. According to the results obtained by implementing and comparing the proposed learning algorithm in two modes within the WASPAS method, the two routes Amol to Babol and Amol to Chamestan are identified as the optimal routes, with weights of 0.2712 and 0.2307, respectively. The weighted importance of the entire selected route has also been calculated as 0.50193 based on the proposed method. The findings of this study can help in decision-making in the field of information management, particularly in contexts involving interconnected or contradictory criteria and uncertain environments.

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Main Subjects

References

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Engineering Management and Soft Computing
Volume 12, Issue 1 - Serial Number 22
January 2026
Pages 205-219

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