Article ID: | iaor20022313 |
Country: | United Kingdom |
Volume: | 39 |
Issue: | 13 |
Start Page Number: | 2817 |
End Page Number: | 2832 |
Publication Date: | Jan 2001 |
Journal: | International Journal of Production Research |
Authors: | Randhawa Sabah U., Jeong Byung Ho |
Keywords: | automated guided vehicles |
This paper considers the dispatching problem associated with operations of automated guided vehicles (AGVs). A multi-attribute dispatching rule for dispatching of an AGV is developed and evaluated. The multi-attribute rule, using the additive weighting method, considers three system attributes concurrently: the remaining space in the outgoing buffer of a workstation, the distance between an idle AGV and a workstation with a job waiting for the vehicle to be serviced, and the remaining space in the input buffer of the destination workstation of a job. A neural network approach is used to obtain dynamically adjusting attribute weights based on the current status of the manufacturing system. Simulation analysis of a job shop is used to compare the multi-attribute dispatching rule with dynamically adjusting attribute weights to the same dispatching rule with fixed attribute weights and to several single attribute rules. Results show that the multi-attribute dispatching rule with the ability to adapt attribute weights to job shop operational conditions provides a better balance among the performance measures used in the study.