F. Ciucci

As engineering systems grow in complexity, the teams that design them require increasingly disparate expertise and must operate in a distributed fashion. At the same time, the teams that design subsystems need to compete and compromise with each other for a limited set of resources. Thus, it becomes crucial to establish a system-level understanding of the trade-offs between subsystems. However, there is little research regarding formal design methods for determining rational designs in a decentralized environment. Lewis and others have developed an effective Game Theoretic approach based on Decision Theory to locate a Nash Equilibrium design with minimum information sharing. This paper presents a design technique to balance tradeoffs between subsystem and system performance by minimizing information sharing between subsystems, thus converging to a set of Pareto Optimal designs. In this research, designers pass a quadratic approximation of each subsystem’s objective functions at each...

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...