Open AccessComparing different ranking functions for solving fuzzy linear programming problems with fuzzy cost coefficients
Author(s) -
Betsabé Pérez Garrido,
Szabolcs Szilárd Sebrek,
Viktoriia Semenova
Publication year - 2021
Publication title -
hungarian statistical review
Language(s) - English
Resource type - Journals
ISSN - 2630-9130
DOI - 10.35618/hsr2021.02.en003
Subject(s) - ranking (information retrieval) , linear programming , mathematical optimization , fuzzy logic , fuzzy number , mathematics , fuzzy mathematics , field (mathematics) , computer science , fuzzy set operations , linear fractional programming , computation , fuzzy classification , fuzzy set , algorithm , machine learning , artificial intelligence , pure mathematics
In many applications of linear programming, the lack of exact information results in various problems. Nevertheless, these types of problems can be handled using fuzzy linear programming. This study aims to compare different ranking functions for solving fuzzy linear programming problems in which the coefficients of the objective function (the cost vector) are fuzzy numbers. A numerical example is introduced from the field of tourism and then solved using five ranking functions. Computations were carried out using the FuzzyLP package implemented in the statistical software R.