Funded Projects
A Collaborative Design Framework under Uncertainty
Funded October 2018
Submitted by Jun Zhuang
Project Team
Jun Zhuang
Industrial and Systems Engineering
Sara Behdad
Mechanical and Aerospace Engineering
Kemper Lewis
Mechanical and Aerospace Engineering
Description
Design has been regarded as a service- and design-driven process for hundreds of years. With the recent development of computer design systems and smart-building techniques, there is a need to study a new performance-based and value-driven design process. Several decision makers and stakeholders are involved in the design cycle, including designers, developers, finance sector, regulators, contractors, manufacturers, and end users. Although those decision makers may have different (and often conflicting) perspectives, values, and resources, they may jointly and subconsciously determine the effectiveness and success of the design process through discussion, negotiation, and contracts. However, designers do not consciously integrate decision analysis and game theory into their design processes. This proposal fills this gap by using normative models (e.g., expected utility theory) to generate robust design strategies, within a game-theoretic framework where descriptive models (e.g., prospect theory) are used to model the stakeholders' behaviors. Multi-attribute utility theory will be used to model the tradeoffs between stakeholders' values for aesthetics, functionality, economics, comfort, sustainability, and safety during the design process. Game theory will be used to study strategic interactions among multiple stakeholders to identify win-win cooperation solutions. The research objectives of this project are to generate a new high-level modeling framework for a multi-agency process for architecture and engineering design. This project will address under-studied questions such as: How to systematically integrate stakeholder preferences into the design process to build a robust partnership while considering that designers or developers may have conflicting preferences and/or behave irrationally? The models will be validated and improved using case studies, simulation, and experiments.
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