An infeasible-start path-following method for monotone LCPs

A path-following infeasible interior-point algorithm for semidefinite programming

We present a new algorithm obtained by changing the search directions in the algorithm given in [8]. This algorithm is based on a new technique for finding the search direction and the strategy of the central path. At each iteration, we use only the full Nesterov-Todd (NT)step. Moreover, we obtain the currently best known iteration bound for the infeasible interior-point algorithms with full NT...

Convergence Analysisof Some Infeasible Path - following Methodsfor the Monotone Semi - Definite Lcp 1

We consider a family of primal/primal-dual/dual search directions for the monotone LCP over the space of n n symmetric block-diagonal matrices. We consider two infeasible predictor-corrector path-following methods using these search directions, with the predictor and corrector steps used either in series (similar to the Mizuno-Todd-Ye method) or in parallel (similar to Mizuno et al./McShane's m...

Infeasible path following algorithms for linear complementarity problems

An Infeasible Interior Point Method for the Monotone Linear Complementarity Problem

Linear complementarity problem noted (LCP) becames in present the subject of many reseach interest because it arises in many areas and it includes the two important domains in optimization:the linear programming (LP) and the convex quadratic (CQP) programming. So the researchers aims to extend the results obtained in (LP) and (CQP) to (LCP). Differents classes of methods are proposed to solve (...

Path Following and Velocity Optimizing for an Omnidirectional Mobile Robot

In this paper, the path following controller of an omnidirectional mobile robot (OMR) has been extended in such a way that the forward velocity has been optimized and the actuator velocity constraints have been taken into account. Both have been attained through the proposed model predictive control (MPC) framework. The forward velocity has been included into the objective function, while the a...