Solving the transportation problem with fuzzy coefficients using genetic algorithms

Author

Lin, Feng-Tse

Author_Institution

Dept. of Appl. Math., Chinese Culture Univ., Taipei, Taiwan

fYear

2009

Firstpage

1468

Lastpage

1473

Abstract

The aim of this work is to introduction a genetic algorithm to solve transportation problem with fuzzy objective functions. The fuzzy objective functions have fuzzy demand and supply coefficients, which are represented as fuzzy numbers. The ranking fuzzy numbers with signed-distance measurement are used for the evaluation and selection of the algorithm. The proposed genetic algorithm is not only simulating fuzzy numbers that representing fuzzy coefficients, but also finding the best solution for the fuzzy transportation problem. The numerical simulation results show that the proposed algorithm is efficient for solving the transportation problem with fuzzy coefficients.

Keywords

fuzzy set theory; genetic algorithms; transportation; fuzzy demand-and-supply coefficient; fuzzy objective function; genetic algorithm; signed-distance measurement; transportation problem; Cost function; Fuzzy sets; Genetic algorithms; Linear programming; Logistics; Numerical simulation; Solids; Supply and demand; Supply chain management; Transportation;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on

Conference_Location

Jeju Island

ISSN

1098-7584

Print_ISBN

978-1-4244-3596-8

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZY.2009.5277202

Filename

5277202