Name
Title | ||
|---|---|---|
A linear programming approximation to the eigenvector method in the analytic hierarchy process. |
Abstract | ||
|---|---|---|
Eigenvector method (EM) is a well-known approach to deriving priorities from pairwise comparison matrices in the analytic hierarchy process (AHP), which requires the solution of a set of nonlinear eigenvalue equations. This paper proposes an approximate solution approach to the EM to facilitate its computation. We refer to the approach as a linear programming approximation to the EM, or LPAEM for short. As the name implies, the LPAEM simplifies the nonlinear eigenvalue equations as a linear programming for solution. It produces true weights for perfectly consistent pairwise comparison matrices. Numerical examples are examined to show the validity and effectiveness of the proposed LPAEM and its significant advantages over a recently developed linear programming method entitled LP-GW-AHP in rank preservation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.ins.2011.07.009 | Inf. Sci. |
Keywords | Field | DocType |
well-known approach,approximate solution approach,linear programming method,nonlinear eigenvalue equation,consistent pairwise comparison matrix,linear programming approximation,eigenvector method,linear programming,pairwise comparison matrix,proposed lpaem,analytic hierarchy process,linear program,eigenvectors,eigenvalues | Linear-fractional programming,Pairwise comparison,Discrete mathematics,Nonlinear system,Matrix (mathematics),Linear programming,Artificial intelligence,Machine learning,Analytic hierarchy process,Eigenvalues and eigenvectors,Mathematics,Computation | Journal |
Volume | Issue | ISSN |
181 | 23 | 0020-0255 |
Citations | PageRank | References |
6 | 0.45 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying-Ming Wang | 1 | 3256 | 166.96 |
| Kwai-Sang Chin | 2 | 1033 | 54.69 |