Please use this identifier to cite or link to this item: https://doi.org/10.1080/10556780500098599
Title: Computation of condition numbers for linear programming problems using Peña's method
Authors: Chai, J.-S.
Toh, K.-C. 
Keywords: Complexity
Conic optimization
Interior-point methods
Linear programming
Renegar condition number
Issue Date: 1-Jun-2006
Source: Chai, J.-S., Toh, K.-C. (2006-06-01). Computation of condition numbers for linear programming problems using Peña's method. Optimization Methods and Software 21 (3) : 419-443. ScholarBank@NUS Repository. https://doi.org/10.1080/10556780500098599
Abstract: We present the computation of the condition numbers for linear programming (LP) problems from the NETLIB suite. The method of Peña [Peña, J., 1998, Computing the distance to infeasibility: theoretical and practical issues. Technical report, Center for Applied Mathematics, Cornell University.] was used to compute the bounds on the distance to ill-posedness ?( d ) of a given problem instance with data d, and the condition number was computed as C ( d )?=?? d ?/?( d ). We discuss the efficient implementation of Peñas method and compare the tightness of the estimates on C ( d ) computed by Peñas method to that computed by the method employed by Ordóñez and Freund [Ordóñez, F. and Freund, R.M., 2003, Computational experience and the explanatory value of condition measures for linear optimization. SIAM Journal on Optimization, 14, 307-333.]. While Peñas method is generally much cheaper, the bounds provided are generally not as tight as those computed by Ordóñez and Freund. As a by-product, we use the computational results to study the correlation between log C ( d ) and the number of interior-point method iterations taken to solve a LP problem instance. Our computational findings on the preprocessed problem instances from NETLIB suite are consistent with those reported by Ordóñez and Freund.
Source Title: Optimization Methods and Software
URI: http://scholarbank.nus.edu.sg/handle/10635/103020
ISSN: 10556788
DOI: 10.1080/10556780500098599
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