Multiagent-based dynamic deployment planning in RTLS-enabled automotive shipment yard

Jindae Kim, Changsoo Ok, Soundar R.T. Kumara, Shang Tae Yee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Real-time vehicle location information enables to facilitate more efficient decision-making in dynamic automotive shipment yard environment. This paper proposes a multiagent-based decentralized decision-making model for the vehicle deployment planning in a shipment yard. A multiagent architecture is designed to facilitate decentralized algorithms and coordinate different agents dynamically. The results of computational experiments show that the proposed deployment model outperforms a current deployment practice with respect to the deployment performance measures.

Original languageEnglish (US)
Title of host publicationAdvances in Artificial Intelligence - 20th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2007, Proceedings
PublisherSpringer Verlag
Pages38-49
Number of pages12
ISBN (Print)9783540726647
DOIs
StatePublished - Jan 1 2007
Event20th Conference of the Canadian Society for Computational Studies of Intelligence, CSCSI, Canadian AI 2007 - Montreal, Canada
Duration: May 28 2007May 30 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4509 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other20th Conference of the Canadian Society for Computational Studies of Intelligence, CSCSI, Canadian AI 2007
CountryCanada
CityMontreal
Period5/28/075/30/07

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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