id: 06042987
dt: j
an: 06042987
au: Wang, Ying-Ming; Chin, Kwai-Sang
ti: A linear programming approximation to the eigenvector method in the
    analytic hierarchy process.
so: Inf. Sci. 181, No. 23, 5240-5248 (2011).
py: 2011
pu: Elsevier Science Inc. (North-Holland), New York, NY
la: EN
cc: 
ut: analytic hierarchy process; multiple criteria decision making; priority
    ranking: linear programming; rank preservation and rank reversal
ci: 
li: doi:10.1016/j.ins.2011.07.009
ab: Summary: 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.
rv: