A multiobjective genetic algorithm based on NSGA II for deriving final ranking from a medium-sized fuzzy outranking relation

Author

Leyva Lopez, Juan Carlos ; Gastelum Chavira, Diego Alonso ; Solano Noriega, Jesus Jaime

Author_Institution

Univ. de Occidente, Culiacan, Mexico

fYear

2014

fDate

9-12 Dec. 2014

Firstpage

24

Lastpage

31

Abstract

In this paper, a heuristic, based on the non dominated sorting genetic algorithm II (NSGA II), is developed to exploit a known fuzzy outranking relation, with the purpose of constructing a recommendation for a medium-sized multicriteria ranking problem. The performance of the proposed evolutionary algorithm is evaluated on a real medium-sized problem. The results indicate that the proposed evolutionary algorithm can effectively be used to solve medium-sized multicriteria ranking problems.

Keywords

fuzzy set theory; genetic algorithms; operations research; NSGA II; evolutionary algorithm; medium-sized fuzzy outranking relation; medium-sized multicriteria ranking problem; medium-sized problem; multiobjective genetic algorithm; nondominated sorting genetic algorithm II; Evolutionary computation; Genetic algorithms; Linear programming; Measurement; Optimization; Sociology; Statistics; fuzzy outranking relations; multicriteria analysis; multiobjective evolutionary algorithms; ranking procedures;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Multi-Criteria Decision-Making (MCDM), 2014 IEEE Symposium on

Conference_Location

Orlando, FL

Type

conf

DOI

10.1109/MCDM.2014.7007184

Filename

7007184