Analytic Central Path, Sensitivity Analysis and Parametric Linear Programming
نویسندگان
چکیده
In this paper we consider properties of the central path and the analytic center of the optimal face in the context of parametric linear programming. We rst show that if the right-hand side vector of a standard linear program is perturbed, then the analytic center of the optimal face is one-side di erentiable with respect to the perturbation parameter. In that case we also show that the whole analytic central path shifts in a uniform fashion. When the objective vector is perturbed, we show that the last part of the analytic central path is tangent to a central path de ned on the optimal face of the original problem.
منابع مشابه
SENSITIVITY ANALYSIS IN LINEAR-PLUS-LINEAR FRACTIONAL PROGRAMMING PROBLEMS
In this paper, we study the classical sensitivity analysis when the right - hand – side vector, and the coefficients of the objective function are allowed to vary.
متن کاملOptimization and Systems Theory CHARACTERIZATION OF THE LIMIT POINT OF THE CENTRAL PATH IN SEMIDEFINITE PROGRAMMING
In linear programming, the central path is known to converge to the analytic center of the set of optimal solutions. Recently, it has been shown that this is not necessarily true for linear semidefinite programming in the absence of strict complementarity. The present paper deals with the formulation of a convex problem whose solution defines the limit point of the central path. This problem is...
متن کاملOn sensitivity of central solutions in semidefinite programming
In this paper we study the properties of the analytic central path of a semidefinite programming problem under perturbation of the right hand side of the constraints, including the limiting behavior when the central optimal solution, namely the analytic center of the optimal set, is approached. Our analysis assumes the primal-dual Slater condition and the strict complementarity condition. Our f...
متن کاملData Envelopment Analysis with Sensitive Analysis and Super-efficiency in Indian Banking Sector
Data envelopment analysis (DEA) is non-parametric linear programming (LP) based technique for estimating the relative efficiency of different decision making units (DMUs) assessing the homogeneous type of multiple-inputs and multiple-outputs. The procedure does not require a priori knowledge of weights, while the main concern of this non-parametric technique is to estimate the optimal weights o...
متن کاملA Predictor-Corrector Path-Following Algorithm for Dual-Degenerate Parametric Optimization Problems
Most path-following algorithms for tracing a solution path of a parametric nonlinear optimization problem are only certifiably convergent under strong regularity assumptions about the problem functions, in particular, the linear independence of the constraint gradients at the solutions, which implies a unique multiplier solution for every nonlinear program. In this paper we propose and prove co...
متن کامل