TY - JOUR
T1 - A Novel Neutrosophic Data Analytic Hierarchy Process for Multi-Criteria Decision Making Method
T2 - A Case Study in Kuala Lumpur Stock Exchange
AU - Tey, Desmond Jun Yi
AU - Gan, Yee Fei
AU - Selvachandran, Ganeshsree
AU - Quek, Shio Gai
AU - Smarandache, Florentin
AU - Son, Le Hoang
AU - Abdel-Basset, Mohamed
AU - Long, Hoang Viet
N1 - Funding Information:
This work was supported by the Ministry of Education, Malaysia, under Grant FRGS/1/2017/STG06/UCSI/03/1.
Publisher Copyright:
© 2013 IEEE.
PY - 2019/4/23
Y1 - 2019/4/23
N2 - This paper proposes a multi-criteria decision making method called the neutrosophic data analytic hierarchy process (NDAHP) for the single-valued neutrosophic set (SVNS). This method is an extension of the neutrosophic analytic hierarchy process (NAHP) designed to handle actual datasets which consist of crisp values. The proposed NDAHP method uses an objective weighting mechanism whereas all other existing versions of the AHP, fuzzy AHP, and other fuzzy based AHP method in literature such as the NAHP and picture fuzzy AHP uses a subjective weighting mechanism to arrive at the decision. This makes the proposed NDAHP method effective as the weightage of the criteria which forms the input of the evaluation matrix are determined in an objective manner using actual data collected for the problem, and hence will not change according to the opinions of different decision makers which are subjective. The proposed NDAHP method is applied to a multi-criteria decision making problem related to the ranking of the financial performance of five public listed petrochemical companies trading in the main board of the Kuala Lumpur Stock Exchange (KLSE). Actual dataset of 15 financial indices for the five petrochemical companies for 2017 obtained from Yahoo! Finance was used in this paper. Following this, a brief comparative study is conducted to evaluate the performance of our NDAHP algorithm against the results of other existing SVNS-based decision making methods in the literature. The results are compared against actual results obtained from KLSE. To further verify the rankings obtained through each method, the Spearman and Pearson ranking tests are carried out on each of the decision making methods that are studied. It is proved that NDAHP produces the most accurate results, and this was further verified from the results of the Spearman and Pearson ranking tests.
AB - This paper proposes a multi-criteria decision making method called the neutrosophic data analytic hierarchy process (NDAHP) for the single-valued neutrosophic set (SVNS). This method is an extension of the neutrosophic analytic hierarchy process (NAHP) designed to handle actual datasets which consist of crisp values. The proposed NDAHP method uses an objective weighting mechanism whereas all other existing versions of the AHP, fuzzy AHP, and other fuzzy based AHP method in literature such as the NAHP and picture fuzzy AHP uses a subjective weighting mechanism to arrive at the decision. This makes the proposed NDAHP method effective as the weightage of the criteria which forms the input of the evaluation matrix are determined in an objective manner using actual data collected for the problem, and hence will not change according to the opinions of different decision makers which are subjective. The proposed NDAHP method is applied to a multi-criteria decision making problem related to the ranking of the financial performance of five public listed petrochemical companies trading in the main board of the Kuala Lumpur Stock Exchange (KLSE). Actual dataset of 15 financial indices for the five petrochemical companies for 2017 obtained from Yahoo! Finance was used in this paper. Following this, a brief comparative study is conducted to evaluate the performance of our NDAHP algorithm against the results of other existing SVNS-based decision making methods in the literature. The results are compared against actual results obtained from KLSE. To further verify the rankings obtained through each method, the Spearman and Pearson ranking tests are carried out on each of the decision making methods that are studied. It is proved that NDAHP produces the most accurate results, and this was further verified from the results of the Spearman and Pearson ranking tests.
KW - analytic hierarchy process (AHP)
KW - multi-criteria decision making
KW - neutrosophic AHP
KW - neutrosophic decision making
KW - Single-valued neutrosophic set
UR - http://www.scopus.com/inward/record.url?scp=85065479406&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2019.2912913
DO - 10.1109/ACCESS.2019.2912913
M3 - Article
AN - SCOPUS:85065479406
SN - 2169-3536
VL - 7
SP - 53687
EP - 53697
JO - IEEE Access
JF - IEEE Access
ER -