Original Paper

International Journal on Interactive Design and Manufacturing (IJIDeM)

, Volume 5, Issue 1, pp 29-44

First online:

Optimization of product configuration assisted by fuzzy agents

  • Egon OstrosiAffiliated withLaboratoire de Recherche Mécatronique 3M, Université de Technologie de Belfort-Montbéliard Email author 
  • , Alain-Jérôme FougèresAffiliated withLaboratoire de Recherche Mécatronique 3M, Université de Technologie de Belfort-Montbéliard

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Configurable product design is a collaborative and distributed process. Supporting collaborative and distributed design for configuration with computer technology is a strategy to enhance the ability of actors to interact with each other and with computational resources. Therefore, from process and product point of views, configurable product design can be assisted by multiagent system. This paper proposes fuzzy agents to assist collaborative and distributed design for optimal configuration. The motivation of this research is that more effective design decisions can be made by fuzzy agents when fuzzy design information is considered in a fuzzy interaction based process and heterogeneous, dynamic adaptive and fuzzy evolving systems. A fuzzy optimal product configuration mathematical formulation is proposed. The modelling and the implementation of an agent-based system complies with this formal basis. In the proposed agent-based system, there are four communities of agents: specification community, function community, physical solution community and production constraint community. During design process, the interactions between agents permit to emerge, first, the consensual physical solutions to configure a product, and secondly, the optimal configuration. The proposed optimization algorithm is inspired from adaptive and distributed routing algorithms used in computer networks. The algorithm allows optimization of product configuration by exchange of the optimal solution agent network information between the neighbour solution agents. A case study is presented to demonstrate the potential of this approach.


Distributed design process Design for configuration Multi agent systems Fuzzy agents Optimal product configuration