- A Polynomial Arc-Search Interior-Point Algorithm for Linear Programming Yaguang Yang(yaguang.yangverizon.net) Abstract: In this paper, ellipse is used to approximate the central path of the linear programming. An interior-point algorithm is devised to search the optimizers along the ellipse. The algorithm is proved to be polynomial with the complexity bound $O(n^{\frac{1}{2}}\log(1/\epsilon))$. Numerical test is conducted for problems in Netlib. For most tested Netlib problems, the result shows that the new algorithm uses less iteration to converge than the Matlab optimization toolbox {\tt linprog} which implements the state-of-art Mehrotra's predictor-corrector algorithm. For all the tested problems, the number of total iterations using the new algorithm is about 20$\%$ fewer than the one using {\tt linprog}. Keywords: Arc-search, interior-point method, polynomial algorithm, linear programming. Category 1: Linear, Cone and Semidefinite Programming (Linear Programming ) Citation: Download: [PDF]Entry Submitted: 11/27/2010Entry Accepted: 12/02/2010Entry Last Modified: 11/27/2010Modify/Update this entry Visitors Authors More about us Links Subscribe, Unsubscribe Digest Archive Search, Browse the Repository Submit Update Policies Coordinator's Board Classification Scheme Credits Give us feedback Optimization Journals, Sites, Societies Optimization Online is supported by the Mathematical Programming Society.