Deliveries optimization by exploiting production traceability information

  • Authors:
  • Simon Tamayo;Thibaud Monteiro;Nathalie Sauer

  • Affiliations:
  • LGIPM EA 3096/INRIA-COSTEAM, ENIM-Université Paul Verlaine-Metz, íle du Saulcy, 57012 METZ, Cedex, France;LGIPM EA 3096/INRIA-COSTEAM, ENIM-Université Paul Verlaine-Metz, íle du Saulcy, 57012 METZ, Cedex, France;LGIPM EA 3096/INRIA-COSTEAM, ENIM-Université Paul Verlaine-Metz, íle du Saulcy, 57012 METZ, Cedex, France

  • Venue:
  • Engineering Applications of Artificial Intelligence
  • Year:
  • 2009

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Abstract

The recent product traceability requirements, particularly in food production chains, demonstrate an industrial need to improve traceability systems. Having real-time access to traceability information allows its exploitation, which is the aim of this work. In this paper, the problem of minimizing the cost of products recall is treated. First the raw material dispersion problem is analyzed, in order to determine a risk-level criterion or ''production criticality''. This criterion is used subsequently to optimize deliveries dispatch with the purpose of minimizing the number of batch recalls in case of crisis. This is achieved by implementing decision-making aid tools based on operational research and artificial intelligence.