Open AccessModeling of linear programming and extended TOPSIS in decision making problem under the framework of picture fuzzy sets
Author(s) -
Muhammad Sarwar Sindhu,
Tabasam Rashid,
Agha Kashif
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0220957
Subject(s) - similarity (geometry) , degree (music) , fuzzy logic , multiple criteria decision analysis , measure (data warehouse) , fuzzy set , linear programming , computer science , mathematics , extension (predicate logic) , construct (python library) , topsis , mathematical optimization , selection (genetic algorithm) , data mining , artificial intelligence , operations research , physics , acoustics , image (mathematics) , programming language
Picture fuzzy sets (PFSs) are comparatively a new extension of fuzzy sets which describe the human opinions that has more answers like acceptance, rejection, neutral and desist, which cannot be correctly presented in fuzzy sets (FSs) and intuitionistic fuzzy sets (IFSs). The PFSs are categorized by three objects, the degree of belonging, the degree of neutral belonging and the degree of non- belonging such that the total of these three degrees must not be more than one. So far, there is no such work presented in the literature which deals with unknown weights of criteria based on PFSs. In the present work, we have developed a linear programming (LP) model to find the exact weights from the given constraints of weights for the criteria and construct a modified distance based on similarity measure between picture fuzzy sets. Then we have utilized this similarity measure to achieve the best option in the multiple criteria decision making (MCDM) problem. Lastly, two practical examples for the selection of alternatives are presented to compare the obtained results with the existing similarity measures.