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A geometric view of parametric linear programming
Authors:Ilan Adler and Renato D C Monteiro
Affiliation:(1) Department of Industrial Engineering and Operations Research, University of California, 94720 Berkeley, CA, USA;(2) Systems and Industrial Engineering Department, University of Arizona, 85721 Tucson, AZ, USA
Abstract:We present a new definition of optimality intervals for the parametric right-hand side linear programming (parametric RHS LP) Problem thetav(lambda) = min{c t x¦Ax =b + lambda¯b,x ge 0}. We then show that an optimality interval consists either of a breakpoint or the open interval between two consecutive breakpoints of the continuous piecewise linear convex function thetav(lambda). As a consequence, the optimality intervals form a partition of the closed interval {lambda; ¦thetav(lambda)¦ < infin}. Based on these optimality intervals, we also introduce an algorithm for solving the parametric RHS LP problem which requires an LP solver as a subroutine. If a polynomial-time LP solver is used to implement this subroutine, we obtain a substantial improvement on the complexity of those parametric RHS LP instances which exhibit degeneracy. When the number of breakpoints of thetav(lambda) is polynomial in terms of the size of the parametric problem, we show that the latter can be solved in polynomial time.This research was partially funded by the United States Navy-Office of Naval Research under Contract N00014-87-K-0202. Its financial support is gratefully acknowledged.
Keywords:Parametric linear programming  Sensitivity analysis  Postoptimality analysis  Linear programming
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