Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 235, Issue 1, Pages 225-232Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2013.10.019
Keywords
Analytic Hierarchy Process; Pair-wise comparison matrix; Cosine similarity measure; Priority vector; Consistency index
Funding
- National Natural Science Foundation of China [71222108]
- Program for New Century Excellent Talents in University [NCET-10-0293]
- Science and Technology Research Program of Chongqing State Educational Commission [KJ131304]
Ask authors/readers for more resources
The derivation of a priority vector from a pair-wise comparison matrix (PCM) is an important issue in the Analytic Hierarchy Process (AHP). The existing methods for the priority vector derivation from PCM include eigenvector method (EV), weighted least squares method (WLS), additive normalization method (AN), logarithmic least squares method (LLS), etc. The derived priority vector should be as similar to each column vector of the PCM as possible if a pair-wise comparison matrix (PCM) is not perfectly consistent. Therefore, a cosine maximization method (CM) based on similarity measure is proposed, which maximizes the sum of the cosine of the angle between the priority vector and each column vector of a PCM. An optimization model for the CM is proposed to derive the reliable priority vector. Using three numerical examples, the CM is compared with the other prioritization methods based on two performance evaluation criteria: Euclidean distance and minimum violation. The results show that the CM is flexible and efficient. (C) 2013 The Authors. Published by Elsevier B.V.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available