A Cloud Model-Based CRITIC-EDAS Decision-Making Approach with Linguistic Information for Marine Ranching Site Selection

Abstract

Modern marine ranching construction has drawn growing attention of relevant planning authorities and enterprises with the potential value of oceans becoming apparent. To satisfy the demand for a successful marine ranching construction, site selection is considered as the first and fundamental procedure. This work aims to help planning authorities find the optimal marine ranching site by introducing a methodological evaluation framework for solving this critical problem. Firstly, the advanced CRiteria Importance Through Inter-criteria Correlation (CRITIC) method is extended by using a cloud model to determine the relative importance of attributes in marine ranching site selection problems. Secondly, the Evaluation based on Distance from Average Solution (EDAS) method is developed by integration with the cloud model to obtain the ranks of alternative sites for marine ranching construction. The proposed cloud model-based CRITIC-EDAS method considers the fuzziness and randomness of the linguistic terms given by experts simultaneously to ensure the scientificity and rationality of decision making. Finally, a real-world marine ranching site selection problem is solved by using the proposed model, where the efficiency and reliability of the proposed model are verified according to the comparison with other traditional multi-attribute decision-making methods.