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2.3.1 Using the Swing Weight Matrix to Weight Multiple Objectives
Author(s) -
Parnell Gregory S.,
Trainor Timothy E.
Publication year - 2009
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2009.tb00949.x
Subject(s) - swing , variation (astronomy) , decision matrix , matrix (chemical analysis) , computer science , value (mathematics) , measure (data warehouse) , range (aeronautics) , mathematical optimization , mathematics , operations research , machine learning , data mining , engineering , mechanical engineering , physics , materials science , astrophysics , composite material , aerospace engineering
Multiobjective decision analysis is used for trade studies and the evaluation of alternative system and architecture designs. Attributes are identified to measure the achievement of each objective. Value (or utility) models are mathematical equations that assess the value (or utility) of a score on an attribute and relative weight of each attribute. One of the challenging concepts is that weights depend on both importance and variation of the range of the attribute. Many analysts, not familiar with the mathematical theory, assess weights using only importance. Several years ago, we developed the swing weight matrix to properly assess weights by explicitly defining importance and variation. A second motivation was to provide a tool for communication with stakeholders and decision makers. This paper presents the swing weight matrix theory, the approaches used to define importance and variation, and some illustrative applications. We conclude with the challenges, improvements, and benefits of the swing weight matrix.