Condition measures and properties of the central trajectory of a linear program

被引:32
作者
Nunez, MA
Freund, RM
机构
[1] Chapman Univ, Sch Business & Econ, Orange, CA 92866 USA
[2] MIT, Alfred P Sloan Sch Management, Cambridge, MA 02139 USA
关键词
linear programming; condition measures; central trajectory; analytic center; interior-point methods; approximate data; approximate solutions; perturbation theory;
D O I
10.1007/BF02680548
中图分类号
TP31 [计算机软件];
学科分类号
081202 [计算机软件与理论]; 0835 [软件工程];
摘要
Given a data instance d = (A, b, c) of a linear program, we show that certain properties of solutions along the central trajectory of the linear program are inherently related to the condition number C(d) of the data instance d = (A, b, c), where C(d) is a scale-invariant reciprocal of a closely-related measure p(d) called the "distance to ill-posedness", (The distance to ill-posedness essentially measures how close the data instance d = (A, b, c) is to being primal or dual infeasible.) We present lower and upper bounds on sizes of optimal solutions along the central trajectory, and on rates of change of solutions along the central trajectory, as either the barrier parameter mu or the data d = (A, b, c) of the linear program is changed. These bounds are all linear or polynomial functions of certain natural parameters associated with the linear program, namely the condition number C(d), the distance to ill-posedness p(d), the norm of the data parallel to d parallel to, and the dimensions m and n. (C) 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.
引用
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页码:1 / 28
页数:28
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