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Design of a decentralized framework for collaborative product design using memetic algorithms

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Abstract

This paper proposes a generalized bi-level decentralized framework to model collaborative design problems over autonomous stakeholders with each having different objectives. At the system level, a system solution derived from the Pareto concept is created. A facilitator agent is introduced to search for Pareto optimal solutions based on a Memetic Algorithm (MA). At the design disciplinary level, design agents representing design teams are introduced to optimize their own objectives. The proposed framework will guide the collaborative designers to converge to Pareto optimal solutions given any forms of design utility functions. The only information exchanged between the two levels is numerical values instead of utility functions. Therefore sensitive (private) design information can be protected. Three comparison experiments are conducted to evaluate the solution quality and explore the applicability of the proposed framework to collaborative design problems.

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Authors and Affiliations

  1. School of Computing, Informatics, Decision Systems Engineering, Arizona State University, Tempe, AZ, 85287-5906, USA

    Fan Li & Teresa Wu

  2. Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, MS, 39762, USA

    Mengqi Hu

Authors
  1. Fan Li
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  2. Teresa Wu
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  3. Mengqi Hu
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Correspondence to Teresa Wu.

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Li, F., Wu, T. & Hu, M. Design of a decentralized framework for collaborative product design using memetic algorithms. Optim Eng 15, 657–676 (2014). https://doi.org/10.1007/s11081-012-9210-6

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  • DOI: https://doi.org/10.1007/s11081-012-9210-6

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