Title :
An Infeasible Primal-Dual Interior-Point Algorithm for Linearly Constrained Convex Optimization Based on a Parametric Kernel Function
Author :
Wang, Guoqiang ; Wang, Baocun ; Fan, Qingduan
Author_Institution :
Coll. of Vocational Technol., Shanghai Univ. of Eng. Sci., Shanghai, China
Abstract :
In this paper we present an infeasible primal-dual interior-point algorithm for linearly constrained convex optimization based on a parametric kernel function, with parameters p isin [0,1] and q ges 1. Numerical test shows that the efficiency of the proposed algorithm and investigates the behavior of the algorithm with different parameters p, q and thetas.
Keywords :
optimisation; infeasible primal-dual interior-point algorithm; linearly constrained convex optimization; parametric kernel function; Books; Constraint optimization; Educational institutions; Equations; Kernel; Prototypes; Testing; Vectors; Interior-point algorithm; Linearly constrained convex optimization; Primal-dual methods;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.156
