Research in Engineering Design

, Volume 23, Issue 1, pp 71–83 | Cite as

An information-passing strategy for achieving Pareto optimality in the design of complex systems

  • Francesco Ciucci
  • Tomonori Honda
  • Maria C. Yang
Original Paper


As engineering systems grow in complexity, it becomes more challenging to achieve system-level designs that effectively balance the trade-offs among subsystems. Lewis and others have developed a well-known, traditional game-theoretic approach for formally modeling complex systems that can locate a Nash equilibrium design with a minimum of information sharing in the form of a point design. This paper builds on Lewis’ work by proposing algorithms that are capable of converging to Pareto-optimal system-level designs by increasing cooperation among subsystems through additional passed information. This paper investigates several forms for this additional passed information, including both quadratic and eigen-based formulations. Such forms offer guidance to designers on how they should change parameter values to better suit the overall system by providing information on directionality and curvature. Strategies for representing passed information are examined in three case studies of 2- and 3-player scenarios that cover a range of system complexity. Depending on the scenario, findings suggest that passing more information generally leads to convergence to a Pareto-optimal set. However, more iterations may be required to reach the Pareto set than if using a traditional game-theoretic approach.


Complex system design Distributed design Design optimization Pareto optimality 



The work described in this paper was supported in part by the National Science Foundation under Award CMMI-0830134. The opinions, findings, conclusions, and recommendations expressed are those of the authors and do not necessarily reflect the views of the sponsors.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Francesco Ciucci
    • 1
  • Tomonori Honda
    • 2
  • Maria C. Yang
    • 3
  1. 1.Heidelberg Graduate School of Mathematical and Computational Methods for the SciencesUniversität HeidelbergHeidelbergGermany
  2. 2.Department of Mechanical EngineeringMassachusetts Institute of TechnologyCambridgeUSA
  3. 3.Department of Mechanical Engineering and Engineering System DivisionMassachusetts Institute of TechnologyCambridgeUSA

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