Journal
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
Volume 14, Issue 10, Pages -Publisher
MDPI
DOI: 10.3390/ijerph14101203
Keywords
meteorological disaster risk assessment; hesitant fuzzy linguistic preference relation (HFLPR); additive consistency; normal distribution; chance-restricted programming; priority
Funding
- National Natural Science Foundation of China [71571104, 71171115, 70901043]
- Qing Lan Project
- Six Talent Peaks Project in Jiangsu Province [2014-JY-014]
- Priority Academic Program Development of Jiangsu Higher Education Institutions
- Natural Science Foundation of Jiangsu, China [BK20141481]
- fifth issue of the '333Project' research projects [BRA2017456]
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As meteorological disaster systems are large complex systems, disaster reduction programs must be based on risk analysis. Consequently, judgment by an expert based on his or her experience (also known as qualitative evaluation) is an important link in meteorological disaster risk assessment. In some complex and non-procedural meteorological disaster risk assessments, a hesitant fuzzy linguistic preference relation (HFLPR) is often used to deal with a situation in which experts may be hesitant while providing preference information of a pairwise comparison of alternatives, that is, the degree of preference of one alternative over another. This study explores hesitation from the perspective of statistical distributions, and obtains an optimal ranking of an HFLPR based on chance-restricted programming, which provides a new approach for hesitant fuzzy optimisation of decision-making in meteorological disaster risk assessments.
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