Title :
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
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;
Conference_Titel :
Simulation Conference, 2000. Proceedings. Winter
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-6579-8
DOI :
10.1109/WSC.2000.899105
