A fuzzy preference programming and weighted influence non-linear gauge system for mission architecture assessment at NASA

Abstract

The selection of a mission architecture is complex due to conflicting and intertwined mission operation criteria. In addition, the uncertainties inherent in human exploration missions make the evaluation process more challenging. This study presents a combination of improved fuzzy preference programming (FPP) and weighted influence non-linear gauge system (WINGS) to efficiently and effectively weigh conflicting and intertwined decision criteria and prioritize mission architecture scenarios at NASA. The improved FPP determines the weights of decision criteria, and the WINGS method considers criteria interdependencies and evaluates the alternative mission architecture scenarios. A numerical example demonstrates the proposed approach’s performance compared to three multi-criteria methods. A case study at the Johnson Space Center shows the applicability and efficacy of the proposed approach.