An interval type-2 fuzzy model for Vehicle Routing Problems in supply chains

Author

Zarandi, M. H Fazel ; Kalhori, M. Rostam Niakan

Author_Institution

Dept. of Ind. Eng., Amirkabir Univ. of Technol., Tehran, Iran

fYear

2012

fDate

6-8 Aug. 2012

Firstpage

1

Lastpage

6

Abstract

In Vehicle Routing Problems (VRPs) one tries to find the best route which begins and terminates at a unique center for a group of vehicles to service a number of customers. This paper presents a VRP in which parameters and continuous decision variables are assumed to be interval type-2 fuzzy sets. Since VRPs are NP-hard, the genetic algorithm (GA) is applied to solve the problem. Computational results are compared with type-1 fuzzy model. They show the efficiency of the proposed model and GA.

Keywords

computational complexity; fuzzy set theory; genetic algorithms; supply chain management; transportation; GA; NP-hard problem; VRP; continuous decision variables; genetic algorithm; interval type-2 fuzzy model; interval type-2 fuzzy sets; supply chains; type-1 fuzzy model; vehicle routing problems; Biological cells; Fuzzy logic; Fuzzy sets; Mathematical model; Routing; Uncertainty; Vehicles; genetic algorithm; interval type-2 fuzzy sets; vehicle routing problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society (NAFIPS), 2012 Annual Meeting of the North American

Conference_Location

Berkeley, CA

ISSN

pending

Print_ISBN

978-1-4673-2336-9

Electronic_ISBN

pending

Type

conf

DOI

10.1109/NAFIPS.2012.6290984

Filename

6290984