Probabilistic AHP and TOPSIS for Multi-Attribute Decision-Making under Uncertainty
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Lafleur, Jarret M.
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Abstract
One challenging aspect in designing complex
engineering systems is the task of making informed design
decisions in the face of uncertainty.1,2 This paper presents a
probabilistic methodology to facilitate such decision making,
in particular under uncertainty in decision-maker
preferences. This methodology builds on the frequently used
multi-attribute decision-making techniques of the
Analytic Hierarchy Process (AHP) and Technique for Order
Preference by Similarity to Ideal Solution (TOPSIS), and it
overcomes some typical limitations that exist in relying on
these deterministic techniques. The methodology is divided
into three segments, each of which consists of multiple
steps. The first segment (steps 1-4) involves setting up the
problem by defining objectives, priorities, uncertainties,
design attributes, and candidate designs. The second
segment (steps 5-8) involves applications of AHP and
TOPSIS using AHP prioritization matrices generated from
probability density functions. The third segment (steps 9-
10) involves visualization of results to assist in selecting a
final design. A key characteristic measured in these final
steps is the consistency with which a design ranks among
the top several alternatives. An example satellite orbit and
launch vehicle selection problem illustrates the
methodology throughout the paper.
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Date
2011-03
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