• 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