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Prior Reduced Fill-In in Solving Equations in Interior Point Algorithms

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dc.creator Birge, John R.
dc.creator Freund, Robert M.
dc.date 2004-05-28T19:33:26Z
dc.date 2004-05-28T19:33:26Z
dc.date 1990-07
dc.date.accessioned 2013-10-09T02:39:01Z
dc.date.available 2013-10-09T02:39:01Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/5318
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description The efficiency of interior-point algorithms for linear programming is related to the effort required to factorize the matrix used to solve for the search direction at each iteration. When the linear program is in symmetric form (i.e., the constraints are Ax b, x > 0 ), then there are two mathematically equivalent forms of the search direction, involving different matrices. One form necessitates factoring a matrix whose sparsity pattern has the same form as that of (A AT). The other form necessitates factoring a matrix whose sparsity pattern has the same form as that of (ATA). Depending on the structure of the matrix A, one of these two forms may produce significantly less fill-in than the other. Furthermore, by analyzing the fill-in of both forms prior to starting the iterative phase of the algorithm, the form with the least fill-in can be computed and used throughout the algorithm. Finally, this methodology can be applied to linear programs that are not in symmetric form, that contain both equality and inequality constraints.
dc.format 329642 bytes
dc.format application/pdf
dc.language en_US
dc.publisher Massachusetts Institute of Technology, Operations Research Center
dc.relation Operations Research Center Working Paper;OR 220-90
dc.subject interior-point algorithm, linear program, factorization, fill-in.
dc.title Prior Reduced Fill-In in Solving Equations in Interior Point Algorithms
dc.type Working Paper


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