Sustainable Cross-Dock Selection Decision Making with a Development of a New Framework Based on Machine Learning and Single-Valued Neutrosophic Set

Document Type : Research Paper

Authors

1 Ph.D. Student Industrial Engineering, Department of Industrial Engineering, Faculty of Engineering and Technology, Shahed University, Tehran, Iran

2 Professor, Department of Industrial Engineering, Faculty of Engineering and Technology, Shahed University, Tehran, Iran

10.22084/ier.2025.30115.2185

Abstract

Cross-docking is a logistics strategy used to collect, sort, and optimally distribute various products from suppliers to customers. Identifying key criteria for the development and location selection of cross-docks is a crucial topic in logistics network management. Choosing a cross-dock location involves both technical and managerial considerations. Cross-docks play a significant role in the supply chain by facilitating the rapid movement of goods from suppliers to customers. The purpose of this research is to provide an integrated multi-criteria decision-making model for cross-dock evaluation and selection. This study employs an integrated approach combining dimensionality reduction methods and multi-criteria decision-making based on a single-valued Neutrosophic set. To reduce the dimension of the decision matrix and determine the weight of the criteria, we introduced a new method based on the Uniform Manifold Approximation and Projection (UMAP) method and correlation coefficient. Additionally, a TODIM method, developed based on the chi-square distance in the single-valued Neutrosophic environment, was used to rank cross-docks. Through a literature review, we identified 18 criteria in 6 main categories, including sustainability and energy criteria for cross-docks. The results demonstrate the effectiveness of the proposed approach in selecting cross-docks, considering both quantitative and qualitative criteria.

Keywords

Main Subjects

References

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Journal of Industrial Engineering Research in Production Systems
Volume 12, Issue 25
March 2025
Pages 47-61

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