Collaborative self-configuration and learning in autonomic computing systems: Applications to supply chain

Hina Arora, Raghu Santanam, Ajay Vinze, Peter Brittenham

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

9 Scopus citations

Abstract

Efficient supply chains should be responsive to demand surges and supply disruptions resulting from internal and external vulnerabilities. Firms can respond to vulnerabilities by either, reallocating and redirecting existing capacity, or, maintaining redundant capacity. Responding to these disruptions depends on efficient real-time decision-making through information sharing and collaboration. The concept of Information Supply Chains captures this focus on information flows between the various entities in the supply chain. In this paper, we use autonomic principles of self-optimization and self-configuration to address demand surges in the context of healthcare information supply chains that have been disrupted by epidemics. We build a prototype system using a multi-agent systems platform and the Autonomic Computing Toolkit, to illustrate how autonomic computing approaches can facilitate resource allocation decisions in responding to public health emergencies.

Original languageEnglish (US)
Title of host publicationProceedings - 3rd International Conference on Autonomic Computing, ICAC 2006
Pages303-304
Number of pages2
StatePublished - Dec 1 2006
Event3rd International Conference on Autonomic Computing, ICAC 2006 - Dublin, Ireland
Duration: Jun 13 2006Jun 16 2006

Publication series

NameProceedings - 3rd International Conference on Autonomic Computing, ICAC 2006
Volume2006

Other

Other3rd International Conference on Autonomic Computing, ICAC 2006
CountryIreland
CityDublin
Period6/13/066/16/06

Keywords

  • Public health emergency
  • Supply chain vulnerability

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Mathematics(all)

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