TY - JOUR
T1 - Rectifying the Inconsistent Fuzzy Preference Matrix in AHP Using a Multi-Objective BicriterionAnt
AU - Girsang, Abba Suganda
AU - Tsai, Chun Wei
AU - Yang, Chu Sing
N1 - Funding Information:
The authors would like to thank the anonymous reviewers for their valuable comments and suggestions on the paper. This work was supported in part by the Ministry of Science and Technology of Taiwan, R.O.C., under Contracts MOST103-2221-E-197-034 and MOST104-2221-E-197-005.
Publisher Copyright:
© 2015, Springer Science+Business Media New York.
PY - 2016/10/1
Y1 - 2016/10/1
N2 - Analytic hierarchy process (AHP) is a decision making tool regarding the criteria analysis to obtain a priority alternative. One of the important issues in comparison matrix of AHP is the consistency. The inconsistent comparison matrix cannot be used to make decision. This paper proposes an algorithm using a modified BicriterionAnt to pursue two objectives intended to rectify the inconsistent fuzzy preference matrix, called MOBAF. The two objectives include minimizing the consistent ratio (CR) and minimizing the deviation matrix, which are in conflict with each other when rectifying the inconsistent matrix. This study uses two pheromone matrices and two heuristic distances matrices to generate the ants tour. To see the performance, MOBAF is implemented to rectify on some inconsistent fuzzy preference matrices. As a result, in addition to being able to rectify the CR, the proposed algorithm also successfully generates some non-dominated solutions that can be considered as optimal solutions.
AB - Analytic hierarchy process (AHP) is a decision making tool regarding the criteria analysis to obtain a priority alternative. One of the important issues in comparison matrix of AHP is the consistency. The inconsistent comparison matrix cannot be used to make decision. This paper proposes an algorithm using a modified BicriterionAnt to pursue two objectives intended to rectify the inconsistent fuzzy preference matrix, called MOBAF. The two objectives include minimizing the consistent ratio (CR) and minimizing the deviation matrix, which are in conflict with each other when rectifying the inconsistent matrix. This study uses two pheromone matrices and two heuristic distances matrices to generate the ants tour. To see the performance, MOBAF is implemented to rectify on some inconsistent fuzzy preference matrices. As a result, in addition to being able to rectify the CR, the proposed algorithm also successfully generates some non-dominated solutions that can be considered as optimal solutions.
UR - http://www.scopus.com/inward/record.url?scp=84944710838&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84944710838&partnerID=8YFLogxK
U2 - 10.1007/s11063-015-9474-x
DO - 10.1007/s11063-015-9474-x
M3 - Article
AN - SCOPUS:84944710838
SN - 1370-4621
VL - 44
SP - 519
EP - 538
JO - Neural Processing Letters
JF - Neural Processing Letters
IS - 2
ER -