The Design of Open Engineering Systems Lab

University at Buffalo - The State University of New York

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Collaborative, Decentralized Engineering Design at the Edge of Rationality_1

Research Area: Research Publication Year: 2008
Type of Publication: Technical Report Keywords: bounded rationality, multi-objective optimization, decentralized design, game theory
Authors: Gurnani, Ashwin; Lewis, Kemper
One perspective of a design process in the engineering design community is that it is largely a process marked and defined by a series of decisions. The fundamental assumption in most developed design decision support methodologies is that decision makers make rational choices; that is, choices that maximize the payoff for the predicted outcome. Decisions that do not maximize the predicted payoff are termed as mistakes or irrational choices and discarded. However, research in behavioral economics, psychology, and cognitive science has studied the human mind and suggested the notion of “bounded rationality” to explain decision errors. Bounded rationality refers to the intrinsic inability of human beings to accurately choose “rational” options prescribed by decision models such as expected utility. This paper extends the notion of bounded rationality within engineering design. Specifically, this paper studies the design of complex systems that require interaction among several different subsystems contributing to the overall product design. For convergent decentralized design problems, rational designers converge to equilibrium solutions that lie at the intersection of their individual rational reaction sets. These equilibrium solutions are usually not Pareto optimal and due to the dynamics of the designers’ interaction in collaborative design, it is rarely possible for them to converge to Pareto optimal solutions. However, when models for bounded rationality are introduced into individual designer behavior, it is seen that the converged solutions can improve the resulting solution. Bounded rational decisions within decentralized design are modeled, and the effects of propagating such decisions within a design process are studied. DOI: 10.1115/1.2988479
Journal of Mechanical Design