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Optimizing Accuracy In Decision Making Using Evolutionary Computing (Paperback)
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Optimizing Accuracy In Decision Making Using Evolutionary Computing (Paperback)
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Analytic Hierarchy Process (AHP) is one of the methods in Decision
Support Systems (DSS). AHP has been criticized mainly for its
priority deviation method, which is one of AHP's main components.
The priority derivation method, also referred to as prioritization
method, is used to derive priorities in order to represent the rank
of alternatives in AHP. There are two approaches to derive
priorities in AHP, which are non-optimization approach and
optimization approach. However, this study found three main
problems in the current prioritization methods which are
inconsistency of the judgment, non-evolutionary computing approach,
and accuracy performance of the prioritization method. In solving
these problems, this study proposed Evolutionary Computing
Procedure for Deriving Priorities (ECPDP). The ECPDP is an EC-based
procedure and derives priorities by solving single objective
optimization problem (SOP) through maximizing the accuracy of the
solution, by using Total Deviation (TD) as an objective function.
The result by using ECPDP is more promising as opposed to the other
prioritization methods in terms of TD value.
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