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Earthquake relief emergency logistics capacity evaluation model integrating cloud generalized information aggregation operators

The aim of this paper is to propose an earthquake relief emergency logistics capacity (ERELC) evaluation model on the basis of cloud model and fuzzy multi-attribute decision making (MADM) method with cloud generalized information aggregation operators, in which two phase procedures are proposed. The first stage utilizes cloud analytic hierarchy process (CAHP) based on the cloud model to obtain the weights of influencing factors; in the second stage, fuzzy comprehensive evaluation (FCE) is applied to determine the overall capacity belongs to. Several new aggregation operators are proposed as well, including the cloud generalized weighted averaging (CGWA) operator and cloud generalized ordered weighted averaging (CGOWA) operator. The main contribution of this paper possesses two points: (1) Using the cloud model can synthetically describe the randomness and fuzziness of qualitative concepts. (2) Establishing a hierarchical model in evaluation of ERELC realizes the transformation from qualitative analysis to quantitative analysis. In addition, a case study is presented to make this application more understandable. We also make comparisons between the fuzzy comprehensive evaluation methods proposed in this paper and some existing ones to confirm its feasibility and rationality.