Evaluating Emergency Response Solutions for Sustainable Community Development by Using Fuzzy Multi-Criteria Group Decision Making Approaches: IVDHF-TOPSIS and IVDHF-VIKOR

Abstract

Emergency management is vital in implementing sustainable community development, for which community planning must include emergency response solutions to potential natural and manmade hazards. To help maintain such solution repository, we investigate effective fuzzy multi-criteria group decision making (FMCGDM) approaches for the complex problems of evaluating alternative emergency response solutions, where weights for decision makers and criteria are unknown due to problem complexity. We employ interval-valued dual hesitant fuzzy (IVDHF) set to address decision hesitancy more effectively. Based on IVDHF assessments, we develop a deviation maximizing model to compute criteria weights and another compatibility maximizing model to calculate weights for decision makers. Then, two ideal-solution-based FMCGDM approaches are proposed: (i) by introducing a synthesized IVDHF group decision matrix into TOPSIS, we develop an IVDHF-TOPSIS approach for fuzzy group settings; (ii) when emphasizing both maximum group utility and minimum individual regret, we extend VIKOR to develop an IVDHF-VIKOR approach, where the derived decision makers' weights are utilized to obtain group decision matrix and the determined criteria weights are integrated to reflect the relative importance of distances from the compromised ideal solution. Compared with aggregation-operators-based approach, IVDHF-TOPSIS and IVDHF-VIKOR can alleviate information loss and computational complexity. Numerical examples have validated the effectiveness of the proposed approaches.

Multiple Attributes Group Decision‐Making Approaches Based on Interval‐Valued Dual Hesitant Fuzzy Unbalanced Linguistic Set and Their Applications

“…To further inspect the effectiveness of formerly developed approaches, in this subsection, we conduct comparative studies with conventional MAGDM approaches of TOPSIS-based methodology [41] and aggregation-operator-based methodology [42], respectively.…”

Multiple Attributes Group Decision-Making under Interval-Valued Dual Hesitant Fuzzy Unbalanced Linguistic Environment with Prioritized Attributes and Unknown Decision-Makers’ Weights

“…After decades of extension and exploitation research [1], multiple attributes decision-making (MADM) approaches have been widely applied to many practical problems in social and technical systems, such as supply chain management [2][3][4][5], business intelligence evaluation [6,7], emergency management [8][9][10], teaching evaluation [11], product design evaluation [12], energy management [13], and waste management [14], among others. Due to increasing complexity in socioeconomic scenarios, and limitedness and uncertainty in human cognition, a single decision-maker is quite often incompetent when confronted with complicated decision-making scenarios.…”

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

“…Although governments have continuously constructed a set of contingency solutions to known disastrous events, economic development programs often break the balance by introducing new threats to public health, such as the epidemic emergency event due to imported Zika virus in the YiWu International Trading Community of China [ 9 ], risks by technology-driven industries (such as nanotextiles, smart-textiles and chemical medicines) [ 10 , 11 ], and risks introduced by disreputable aluminum ore mining industries in developing countries. Therefore, in order to get well prepared to respond to potential risks, governments at different levels are behooved to establish decision support systems for emergency management [ 12 , 13 ], and to adopt decision-making procedures for risk assessment and emergency response solutions evaluation (ERSE) [ 1 , 13 ].…”

“…For the reason that ERSE activities generally involve a group of stakeholders to comprehensively consider response solutions under a set of criteria, ERSE is normally conceptualized as a type of multi-criteria group decision making (MCGDM) problem [ 1 , 9 , 14 , 15 , 16 , 17 ], in which decision preferences are often uncertain due to problem complexity. To effectively accommodate the uncertain multi-criteria decision making problems, many efforts have been expended [ 18 ], such as the extended ELECTRE-III under interval-valued intuitionistic fuzzy environment [ 19 ], complex proportional assessment (COPRAS) approaches [ 20 , 21 ], the additive ratio assessment (ARAS) methods [ 22 , 23 ], Multiobjective Optimisation by Ratio Analysis Plus Full Multiplicative Form (MULTIMOORA) [ 24 , 25 , 26 ], etc.…”

“…Because of its merits in expressing hesitant information, HFS has been widely studied for more complex situations, including the dual hesitant fuzzy set (DHFS) [ 29 ] that contains both possible membership degrees and non-membership degrees, interval-valued dual hesitant fuzzy set (IVDHFS) [ 30 , 31 ] that more practically allows possible membership or non-membership degrees to be interval values. Most recently, aiming at the complex ERSE problems where decision hesitancy exists and weighting information for both criteria and decision makers cannot be determined in advance, Zhang et al [ 9 ] developed two approaches that utilized IVDHFS to elicit hesitant fuzzy evaluations. However, in their approaches, the distance measure of IVDHFS that was adopted to derive weighting information obeyed a classic complementing method [ 32 , 33 ], i.e., optimistic or pessimistic mechanism of filling the unmatched membership degree set or non-membership degree set in any two compared interval-valued dual hesitant fuzzy elements, but apparently, the value-filling mechanism will inevitably cause some information distortion in contrast with the original preference information.…”