Title :
Evolutionary tuning of a fuzzy dispatching system for automated guided vehicles
Author :
Tan, K.K. ; Tan, K.C. ; Tang, K.Z.
Author_Institution :
Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore
fDate :
8/1/2000 12:00:00 AM
Abstract :
This paper develops a novel genetic algorithm (GA) based methodology for optimal tuning of a reported fuzzy dispatching system for a fleet of automated guided vehicles in a flexible manufacturing environment. The reported dispatching rules are transformed into a continuously adaptive procedure to capitalize the on-line information available from a shop floor at all times. Simulation results obtained show that the GA is very powerful and effective to achieve optimal fuzzy dispatching rules for higher shop floor productivity and operational efficiency
Keywords :
Automatic guided vehicles; Dispatching; Evolutionary computation; Genetic algorithms; Transportation; automated guided vehicles; flexible manufacturing environment; fuzzy dispatching system; genetic algorithm; optimal tuning; Dispatching; Flexible manufacturing systems; Fuzzy logic; Fuzzy systems; Genetic algorithms; Job shop scheduling; Manufacturing automation; Productivity; Pulp manufacturing; Vehicles;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.865187