Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator
This paper tries to point out that the aggregation weights in linguistic hybrid geometric averaging operator will dominate the final result of the ranking for alternatives. We examined the linguistic hybrid geometric averaging operator that was proposed by previous studies and found it contained s...
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doaj-515503f7d014451c94aa11d84582b1c72020-11-24T21:18:35ZengOperations research society of TaiwanInternational Journal of Operations Research1813-713X1813-71482017-09-01144177185Aggregation Weights for Linguistic Hybrid Geometric Averaging OperatorJones Pi-Chang Chuang0Scott Shu-Cheng Lin1Peterson Julian2Department of Traffic Science, Central Police University No.56, Shujen Rd., Takang Vil., Kueishan District, Taoyuan City 33304, Taiwan Department of Hotel Management, Lee-Ming Institute of Technology Shanchuku, T'Ai-Pei, TaiwanDepartment of Traffic Science, Central Police University No.56, Shujen Rd., Takang Vil., Kueishan District, Taoyuan City 33304, Taiwan This paper tries to point out that the aggregation weights in linguistic hybrid geometric averaging operator will dominate the final result of the ranking for alternatives. We examined the linguistic hybrid geometric averaging operator that was proposed by previous studies and found it contained several questionable results. The major defect of the previous approach was that it failed to demonstrate two core factors: accuracy and speed, both of which have been explicitly uncovered and discussed in the study. With previous work the pivotal and dominant element, distribution of weights, in finding subjectively by decision maker of linguistic hybrid geometric averaging operators for group decision-making problems, lacks solid foundation and is unjustified. Here we provide the mathematical rationale and reliable advices, to point out that deficiency. In addition, we have detected and rectified some redundancies of operational laws in the procedure of previous study due to the improper utilization of negative operators. It certainly should be noted that the careless applications of those highly dependant operators may significantly diminish the efficiency and performance of entire mechanism for decision making under fuzzy environment. We develop an easy aggregation approach based on the arithmetic mean to solve the most favorable alternative problem. A comprehensive numerical examination of 1296 tests supports our result.http://www.orstw.org.tw/ijor/vol14no4/IJOR2017_vol14_no4_p177_p185.pdfDecision-makingLinguistic preference relation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jones Pi-Chang Chuang Scott Shu-Cheng Lin Peterson Julian |
spellingShingle |
Jones Pi-Chang Chuang Scott Shu-Cheng Lin Peterson Julian Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator International Journal of Operations Research Decision-making Linguistic preference relation |
author_facet |
Jones Pi-Chang Chuang Scott Shu-Cheng Lin Peterson Julian |
author_sort |
Jones Pi-Chang Chuang |
title |
Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator |
title_short |
Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator |
title_full |
Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator |
title_fullStr |
Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator |
title_full_unstemmed |
Aggregation Weights for Linguistic Hybrid Geometric Averaging Operator |
title_sort |
aggregation weights for linguistic hybrid geometric averaging operator |
publisher |
Operations research society of Taiwan |
series |
International Journal of Operations Research |
issn |
1813-713X 1813-7148 |
publishDate |
2017-09-01 |
description |
This paper tries to point out that the aggregation weights in linguistic hybrid geometric averaging
operator will dominate the final result of the ranking for alternatives. We examined the linguistic hybrid geometric
averaging operator that was proposed by previous studies and found it contained several questionable results. The
major defect of the previous approach was that it failed to demonstrate two core factors: accuracy and speed, both of
which have been explicitly uncovered and discussed in the study. With previous work the pivotal and dominant element,
distribution of weights, in finding subjectively by decision maker of linguistic hybrid geometric averaging operators
for group decision-making problems, lacks solid foundation and is unjustified. Here we provide the mathematical
rationale and reliable advices, to point out that deficiency. In addition, we have detected and rectified some
redundancies of operational laws in the procedure of previous study due to the improper utilization of negative
operators. It certainly should be noted that the careless applications of those highly dependant operators may
significantly diminish the efficiency and performance of entire mechanism for decision making under fuzzy
environment. We develop an easy aggregation approach based on the arithmetic mean to solve the most favorable
alternative problem. A comprehensive numerical examination of 1296 tests supports our result. |
topic |
Decision-making Linguistic preference relation |
url |
http://www.orstw.org.tw/ijor/vol14no4/IJOR2017_vol14_no4_p177_p185.pdf |
work_keys_str_mv |
AT jonespichangchuang aggregationweightsforlinguistichybridgeometricaveragingoperator AT scottshuchenglin aggregationweightsforlinguistichybridgeometricaveragingoperator AT petersonjulian aggregationweightsforlinguistichybridgeometricaveragingoperator |
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1726008361656254464 |