A GIS-LP integrated approach for the logistics hub location problem. (August 2020)

• Record Type: Journal Article
• Authors: Shahparvari, Shahrooz; Nasirian, Araz; Mohammadi, Alireza; Noori, Sepideh; Chhetri, Prem
• Is Part Of: Computers & industrial engineering. Volume 146(2020)
• Publication Date: 2020-08
• Subjects: Logistics Hub Location Problem -- Heuristic (LHLP) -- Mixed Integer Quadratic constrained Programming (MIQCP) -- Geographic Information System (GIS) -- Multiple-criteria decision-making (MCDM) -- PROMETHEE; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106488
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: An MCDM-based (VIKOR) has been adjusted and integrated using Fuzzy concept in a GIS environment. A clustering linear programming method has been developed to find the suitable location for the LHLP. K-means heuristic-based algorithm has been developed and validated to obtain the results in very large case-studies. A comprehensive pairwise analysis on the output of the GIS and LP have been examines by the PROMETHEE II method. Abstract: This study solves the location problem for establishing a logistics hub that serves as a consolidation center to distribute urban freight in the North Western Region of Iran. A novel multi-method approach is developed to implement a two-stage research framework. GIS-embedded multi-criteria decision tools are applied to identify potential regions; a K-means based heuristic approach is developed to select five potential sites; and PROMETHEE, multi-criteria decision-making tool, is implemented to ascertain the best possible site for establishing logistics hub. "Višekriterijumska Optimizacija i kompromisno Rešenje" (VIKOR) method is applied on multiple region-specific criteria to identify potential regions suitable for the logistics hub. A novel clustering Mixed Integer Quadratic constrained Programming (MIQCP) is then applied for clustering the centriods representing the most suitable sites.A K-means heuristic approach is also implemented as an alternative clustering solution approach to improve computational time for data processing. Several criteria such as cost, profit, health effects, political matters and regulations are then used to identify the best site using PROMETHEE method. The outputs of this study may inform evidence based decision-making help to solve highly complex, multi-scaled, and multi-criteria location problems. Municipal authorities, in conjunction with industry, can apply this framework to identify the best compromised site for establishing a regional logistics hub, which in turn help reduce costs, improve logistic efficiency and enhance regional performance.