Solving Large-Scale Linear Programs by Interior-Point Methods
Under the MATLAB Environment
Yin Zhang
In this paper, we describe our implementation of a primal-dual
infeasible-interior-point algorithm for large-scale linear programming
under the MATLAB environment. The resulting software is called LIPSOL
-- Linear-programming Interior-Point SOLvers. LIPSOL is designed to
take the advantages of MATLAB's sparse-matrix functions and external
interface facilities, and of existing Fortran sparse Cholesky codes.
Under the MATLAB environment, LIPSOL inherits a high degree of
simplicity and versatility in comparison to its counterparts in
Fortran or C language. More importantly, our extensive computational
results demonstrate that LIPSOL also attains an impressive performance
comparable with that of efficient Fortran or C codes in solving
large-scale problems. In addition, we discuss in detail a technique
for overcoming numerical instability in Cholesky factorization at the
end-stage of iterations in interior-point algorithms.
Technical Report, Mathematics Department,
University of Maryland Baltimore County,
March, 1996.
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