A novel three-stage fuzzy GIS-MCDA approach to the dry port site selection problem: A case study of Shahid Rajaei Port in Iran. (June 2022) - Raad, Nima Golghamat; Rajendran, Suchithra; Salimi, Soheila
Highlights: Seaport congestion leads to increase in shipping cost, accidents and air pollution. Dry ports are used in tandem with coastal ports to alleviate this congestion. This study proposes a novel three-stage approach for dry port site selection. MCDA-GIS is used long with fuzzy SWARA MULTIMOORA technique. Proposed framework is more robust than existing model in the literature. Abstract: Seaport congestion not only leads to an increase in shipping freight cost, but also results in an increase in traffic, accident rates, stress and environmental pollution of coastal cities. To alleviate these challenges, dry ports, terminals located in the hinterland of coastal ports, are being used in tandem with seaport operations. The necessary transportation infrastructure such as roads, railways, and airports are provided near these ports, and customers can send and receive their goods using these facilities. The site selection of dry ports is a strategic decision associated with the high cost of building a facility. This paper is the first to propose a three-stage approach in which an integrated MCDA-GIS (Multi-Criteria Decision-Making based Geographic Information System) methodology consisting of fuzzy SWARA (Stepwise Weight Assessment Ratio Analysis) GIS-based site selection with fuzzy functions, and an augmented version of fuzzy MULTIMOORA (Multi-Objective Optimization on the basis of Ratio Analysis plus full multiplicative form), is used to weigh the decision-making criteria, identify potential sites, evaluate those alternatives, respectively. A case study is considered for selecting dry ports in the Shahid Rajaee port of Iran, located in the center of the south-north transport corridor in a region that is responsible for almost 50% of Iran's trade volume. The performance of the proposed approach is compared with the most common fuzzy AHP method in the literature. It is observed that the developed method performs less complex and more robust than the prior technique.