A multi-agent system of adaptive production networks

ABSTRACT

Production networks of firms linked by supply-customer relationships embedded in a geographical space are among the phenomena not yet well understood by practitioners and scientists. A production network can be defined as a network of autonomous or semiautonomous business entities collectively responsible for procurement, manufacturing and distribution activities associated with one or more families of related products. Such networks are highly non-linear and exhibit complex behavior through the interplay of their structure, environment and function, this complexity making it difficult to manage, control or even predict them. Production networks, supply chains and their management have received considerable attention from researchers in various disciplines over the past two decades. Agent-based modeling (ABM) and simulation are regarded as one of the best candidates for addressing different aspects of these networks. Indeed, ABMs allow the study of complex systems such as production networks, from a micro-macro evolutionary modeling perspective. They are able to take into account both the issue of heterogeneity and autonomy of the agents, the relevance of their temporal-spatial dynamic relations and the emergent evolutionary nature of collective phenomena.

REFERENCES

• 1: Zahia Guessoum , Jean-Pierre Briot, From Active Objects to Autonomous Agents, IEEE Concurrency, v.7 n.3, p.68-76, July 1999 [doi>10.1109/4434.788781]
• 2: S. Hamichi, Z. Guessoum, and D. Mangalagiu. A multi-agent system of adaptive production networks. Internal report, LIP6, 2008. available at http://www-poleia.lip6.fr/~guessoum/TR01.pdf.
• 3: G. Weisbuch and S. Battiston. From production networks to geographical economics. JEBO, 64:448--469, 2007.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Heuristic methods
  I.6 SIMULATION AND MODELING
      I.6.5 Model Development
          Subjects: Modeling methodologies

General Terms:
Algorithms, Design, Theory

Keywords:
firms behavior, multi-agent simulation, pattern emergence, price mechanisms, production networks