Simulation of an evolutionary tuned fuzzy dispatching system for automated guided vehicles

Author

Tan, K.K. ; Tang, K.Z.

Author_Institution

Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore

Volume

2

fYear

2000

fDate

2000

Firstpage

1339

Abstract

This paper presents the development and simulation of a novel genetic algorithm (GA) based methodology applied to optimal tuning of a fuzzy dispatching system for a fleet of automated guided vehicles in a flexible manufacturing environment. The dispatching rules are further transformed into a continuously adaptive procedure to capitalize the online information available from a shop floor at all times. The entire problem is simulated using MATLAB/SIMULINK. The simulation results obtained show that GA is an efficient and effective tool to achieve optimal performance for the well-known NP-complete scheduling problem

Keywords

automatic guided vehicles; computational complexity; flexible manufacturing systems; fuzzy control; genetic algorithms; MATLAB; NP-complete scheduling problem; SIMULINK; automated guided vehicles; continuously adaptive procedure; evolutionary tuned fuzzy dispatching system simulation; flexible manufacturing environment; fuzzy dispatching system; genetic algorithm; online information; optimal tuning; simulation; Dispatching; Flexible manufacturing systems; Fuzzy systems; Genetic algorithms; Job shop scheduling; MATLAB; Manufacturing automation; Pulp manufacturing; Vehicles; Virtual manufacturing;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference, 2000. Proceedings. Winter

Conference_Location

Orlando, FL

Print_ISBN

0-7803-6579-8

Type

conf

DOI

10.1109/WSC.2000.899105

Filename

899105