TY - JOUR
T1 - Ant algorithm for modifying an inconsistent pairwise weighting matrix in an analytic hierarchy process
AU - Girsang, Abba Suganda
AU - Tsai, Chun Wei
AU - Yang, Chu Sing
N1 - Funding Information:
The authors would like to thank the editors and anonymous reviewers for their valuable comments and suggestions on the paper that greatly improve the quality of the paper This work was supported in part by the Ministry of Science and Technology of Taiwan, R.O.C., under Contracts NSC102-2221-E-041-006 and NSC 102-2219-E-006-001.
Publisher Copyright:
© 2014, Springer-Verlag London.
PY - 2014/2
Y1 - 2014/2
N2 - One important issue in the analytic hierarchy process (AHP) is confirming the consistency of comparison matrix to verify the logical respondent opinion. As inconsistent comparison matrix cannot be used as reference to make decisions, this paper proposes a method using an ant algorithm to modify an inconsistent pairwise weight matrix to be consistent in AHP, called ANTAHP. This method employs the matrix element as the path in an ant colony optimization to construct the tour. By laying pheromone information on their path, the ants can find the optimal matrix (or tour), which satisfies the consistency and closer to the original judgment of the decision makers. The experimental results demonstrate that the proposed algorithm is able to make consistent matrices, as well as minimize the difference index.
AB - One important issue in the analytic hierarchy process (AHP) is confirming the consistency of comparison matrix to verify the logical respondent opinion. As inconsistent comparison matrix cannot be used as reference to make decisions, this paper proposes a method using an ant algorithm to modify an inconsistent pairwise weight matrix to be consistent in AHP, called ANTAHP. This method employs the matrix element as the path in an ant colony optimization to construct the tour. By laying pheromone information on their path, the ants can find the optimal matrix (or tour), which satisfies the consistency and closer to the original judgment of the decision makers. The experimental results demonstrate that the proposed algorithm is able to make consistent matrices, as well as minimize the difference index.
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U2 - 10.1007/s00521-014-1630-0
DO - 10.1007/s00521-014-1630-0
M3 - Article
AN - SCOPUS:84921699325
VL - 26
SP - 313
EP - 327
JO - Neural Computing and Applications
JF - Neural Computing and Applications
SN - 0941-0643
IS - 2
ER -