Please use this identifier to cite or link to this item:
|Title:||Evolutionary tuning of a fuzzy dispatching system for automated guided vehicles|
|Authors:||Tan, K.K. |
|Citation:||Tan, K.K., Tan, K.C., Tang, K.Z. (2000-08). Evolutionary tuning of a fuzzy dispatching system for automated guided vehicles. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 30 (4) : 632-636. ScholarBank@NUS Repository. https://doi.org/10.1109/3477.865187|
|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.|
|Source Title:||IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Oct 12, 2018
WEB OF SCIENCETM
checked on Oct 3, 2018
checked on Oct 6, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.