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Abstract

In this paper, we introduce a new approach to autonomous decentralized shop floor routing. Our system, which we call Ant Colony Control ($\mbox{AC}^2$), applies the analogy of a colony of ants foraging for food to the problem of dynamic shop floor routing. In this system, artificial ants use only indirect communication to make all shop routing decisions by altering and reacting to their dynamically changing common environment through the use of simulated pheromone trails. For simple factory layouts, we show that the emergent behavior of the colony is comparable to using the optimal routing strategy. Furthermore, as the complexity of the factory layout is increased, we show that the adaptive behavior of $\mbox{AC}^2$ evolves local decision making policies that lead to near-optimal solutions from the standpoint of global performance.

Keywords

ant colonies, decentralized scheduling, shop floor routing

Notes

Associated Center(s) / Consortia: Center for Integrated Manfacturing Decision Systems

Associated Lab(s) / Group(s): Reliable Autonomous Systems Lab and Intelligent Coordination and Logistics Laboratory

Associated Project(s): Federation of Intelligent Robotic Explorers Project and Distributed Coordination of Resources

Number of pages: 8

Text Reference

Vincent Cicirello and Stephen Smith , "Ant Colony Control for Autonomous Decentralized Shop Floor Routing," ISADS-2001: Fifth International Symposium on Autonomous Decentralized Systems, March, 2001, pp. 383 - 390.

BibTeX Reference

@inproceedings{Cicirello_2001_3454,
   author = "Vincent Cicirello and Stephen {Smith }",
   title = "Ant Colony Control for Autonomous Decentralized Shop Floor Routing",
   booktitle = "ISADS-2001: Fifth International Symposium on Autonomous Decentralized Systems",
   pages = "383 - 390",
   publisher = "IEEE Computer Society",
   month = "March",
   year = "2001",
}

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