A new framework for health-care waste disposal alternative selection under multi-granular linguistic distribution assessment environment

Abstract The choice of suitable health-care waste disposal alternative (HCWDA) is critical to health-care waste management and has recently attracted much attention for both researchers and practitioners. During the evaluation of HCWDA, there usually exists incomplete and uncertain information, and the experts cannot easily express their judgments on the alternatives with precise values. This paper presents a new framework based on the evaluation based on distance from average solution (EDAS) method for selecting desirable health-care waste disposal alternative(s). Multi-granular linguistic distribution assessments are adopted by experts to assess the ratings of alternatives and subjective weights of criteria. To reflect accurately the reality, an approach is firstly proposed to determine the experts’ weights with respect to each criterion based on Dice similarity measure. Secondly, to determine the objective weights of criteria a combination of the minimum variance and the maximizing deviation methods are introduced, from it the comprehensive weights of criteria will be derived. Thirdly, the traditional EDAS method is extended to rank and select reasonable HCWDA. Finally, a numerical example of the proposed framework is provided, and its validity is verified by comparing it with previous methods.