DocumentCode
1362033
Title
Status-based Routing in Baggage Handling Systems: Searching Verses Learning
Author
Johnstone, Michael ; Creighton, Doug ; Nahavandi, Saeid
Author_Institution
Center for Intell. Syst. Res., Deakin Univ., Waurn Ponds, VIC, Australia
Volume
40
Issue
2
fYear
2010
fDate
3/1/2010 12:00:00 AM
Firstpage
189
Lastpage
200
Abstract
This study contributes to work in baggage handling system (BHS) control, specifically dynamic bag routing. Although studies in BHS agent-based control have examined the need for intelligent control, but there has not been an effort to explore the dynamic routing problem. As such, this study provides additional insight into how agents can learn to route in a BHS. This study describes a BHS status-based routing algorithm that applies learning methods to select criteria based on routing decisions. Although numerous studies have identified the need for dynamic routing, little analytic attention has been paid to intelligent agents for learning routing tables rather than manual creation of routing rules. We address this issue by demonstrating the ability of agents to learn how to route based on bag status, a robust method that is able to function in a variety of different BHS designs.
Keywords
airports; control engineering computing; intelligent control; learning (artificial intelligence); materials handling; multi-agent systems; agent-based control; baggage handling system control; dynamic bag routing problem; intelligent control; learning routing tables; status-based routing; Airport operations; materials handling; reinforcement learning (RL); search methods;
fLanguage
English
Journal_Title
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher
ieee
ISSN
1094-6977
Type
jour
DOI
10.1109/TSMCC.2009.2035519
Filename
5357429
Link To Document