UPSI Digital Repository (UDRep)
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UPSI Digital Repository (UDRep)
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| Abstract : Universiti Pendidikan Sultan Idris |
| The purpose of this research was to design and develop a new multi-criteria decision- making (MCDM)
method called Fuzzy Decision by Opinion Score Method (FDOSM) to help overcome the problems of
MCDM methods based on the idea of an ideal solution This research used an experimental
research design with which FDOSM was applied to individual and group contexts. Essentially,
FDOSM contains three main blocks, namely the input data block, data transfer block, and data
processing block. For the data processing block, three sets of experiments were carried out to
optimize the parameters of the proposed method. The first experiment dealt with three
different configurations, namely Direct aggregation, Compromise Rank, and Distance
measurement, of a single decision maker. Direct aggregation with arithmetic mean is the main
configuration recommended for comparing the results of different experiments.
However, if the maximum utility is important to the decision maker, compromise ranking
would be the proper configuration. The second experiment focused on the process of
Group Fuzzy Decision by Opinion Score Method (G- FDOSM) with two different configurations,
namely internal and external aggregation. The main finding of G-FDOSM experiment showed the results
of internal and external configurations were close, with the ratio of the closeness of the
experimental results of G-FDOSM with 90 alternatives being 71.02%. However, external
aggregation was deemed more appropriate for compromise ranking. The third experiment
involved several different case studies to examine the suitability of FDOSM in solving different
MCDM problems. The results showed that, compared to the ideal solution, the best player (P16)
achieved a ratio of 58.3% from the ideal solution, which was considered to be the best ratio among
other players for the sports science case study. For the GPS case study, experimental results
showed the best solution was m8 with a ratio of 67% from the ideal solution. Overall, the results
of FDOSM and G-FDOSM were close to the human’s opinions, suggesting that arithmetic mean is the
most suitable aggregation operator for all the experiments and FDOSM can adopt different fuzzy
membership. Furthermore, reference comparison used with FDOSM can be implemented more
efficiently compared to the use of the pairwise comparison of the Analytic Hierarchy Process and
the Best-Worst Method. In conclusion, the proposed FDOSM had been successfully modulated
mathematically, tested with different numerical examples, and
compared to other MCDM methods.
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