Tackling Complex Emergency Response Solutions Evaluation Problems in Sustainable Development by Fuzzy Group Decision Making Approaches with Considering Decision Hesitancy and Prioritization among Assessing Criteria

Abstract

In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager’s prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches.

Special Issue “Decision Models in Green Growth and Sustainable Development”

“…Taking into account of the sensitivity of various microorganisms to ozone, Brodowska et al [ 49 ] constructed a microbial model to preserve different strains of food. Considering the hesitancy of decision-making problems and the priority of evaluation criteria, Qi et al [ 50 ] adopted a fuzzy GDM method to deal with the evaluation of complex emergency response solutions. Lin and Wang [ 51 ] constructed a linguistic multi-attribute GDM linear model based on risk preference with an application to the selection of low-carbon tourist destinations.…”

Humanitarian Rescue Scheme Selection under the Covid-19 Crisis in China: Based on Group Decision-Making Method

“…Yin et al [10] proposed gray relational multi-attribute group decision-making methods with respect to multi-attribute group decision-making problems, where attribute values take the form of interval gray trapezoid fuzzy linguistic variables, and the expert weight and the attribute weight are determined by the maximum deviation method. Aiming at the special type of emergency response solution evaluation problems that hold the two characteristics, Qi et al [11] investigated effective multiple criteria group decision making (MCGDM) approaches by hiring an interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy, and they defined a fuzzy entropy measure for IVDHFS so that its derivative decision models could avoid potential information distortion in models based on classic IVDHFS distance measures with a subjective supplementing mechanism. Liang et al [12] proposed a novel emergency decision method, developing the linguistic distribution power average (LDPA) and linguistic distribution weighted power average (LDWPA) operators to aggregate the subgroups' evaluations.…”

A Novel Multiattribute Decision-Making Method Based on Point–Choquet Aggregation Operators and Its Application in Supporting the Hierarchical Medical Treatment System in China

“…For example, Tang et al [ 1 ] proposed an algorithm for group decision making with incomplete hesitant fuzzy linguistic preference relations and applied it to flood disaster risk evaluation. Qi [ 2 ] developed two effective multicriteria decision making (MCDM) approaches based on defined prioritized average aggregation operators and applied them to tackle complex emergency response solutions evaluation problems. Lin [ 3 ] proposed a linear program and a procedure for solving linguistic MADM problems with risk preferences and incomplete weight information, and further applied it to low-carbon tourism destination selection.…”