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Selecting the Low-Carbon Tourism Destination: Based on Pythagorean Fuzzy Taxonomy Method
- Source :
- Mathematics, Vol 8, Iss 832, p 832 (2020), Mathematics; Volume 8; Issue 5; Pages: 832
- Publication Year :
- 2020
- Publisher :
- MDPI AG, 2020.
-
Abstract
- Low-carbon tourism plays the increasingly significant role in carbon emission reduction and natural environmental protection. The choice of low-carbon tourist destination (LCTD) often involves the multiple attributes or criteria and can be regarded as the corresponding multiple attribute group decision making (MAGDM) issues. Since the Pythagorean fuzzy sets (PFSs) could well depict uncertain information or fuzzy information and cope with the LCTD selection, thus this essay develops a framework to tackle such MAGDM issues under the Pythagorean fuzzy environment. In this essay, due to few methods can compare with different alternatives along with their advantages from designed attributes, therefore, to overcome this challenge, the taxonomy method is utilized to integrate with PFSs. What’s more, the entropy method is also utilized to determine the attribute weights. Eventually, an application related to LCTD selection and some comparative analysis have been given to demonstrate the superiority of the designed method. The results illustrate that the designed framework is useful for identifying optimal tourist destination among the potential tourist destinations.
- Subjects :
- 0209 industrial biotechnology
Operations research
Computer science
General Mathematics
02 engineering and technology
Fuzzy logic
020901 industrial engineering & automation
0202 electrical engineering, electronic engineering, information engineering
Computer Science (miscellaneous)
Entropy (information theory)
Engineering (miscellaneous)
Multiple attribute
Taxonomy method
multiple attribute group decision making (MAGDM)
Pythagorean fuzzy sets (PFSs)
information entropy
low-carbon tourist destination selection
lcsh:Mathematics
Pythagorean theorem
lcsh:QA1-939
Group decision-making
Pythagorean fuzzy sets
Tourist destinations
020201 artificial intelligence & image processing
Tourism
Subjects
Details
- Language :
- English
- ISSN :
- 22277390
- Volume :
- 8
- Issue :
- 832
- Database :
- OpenAIRE
- Journal :
- Mathematics
- Accession number :
- edsair.doi.dedup.....2b64b7e2df7069fb94a561298fb64577