On implementing a primal-dual interior-point method for conic quadratic optimization
نویسندگان
چکیده
منابع مشابه
On implementing a primal-dual interior-point method for conic quadratic optimization
Conic quadratic optimization is the problem of minimizing a linear function subject to the intersection of an affine set and the product of quadratic cones. The problem is a convex optimization problem and has numerous applications in engineering, economics, and other areas of science. Indeed, linear and convex quadratic optimization is a special case. Conic quadratic optimization problems can ...
متن کاملA Primal-dual Interior Point Algorithm for Convex Quadratic Programs
In this paper, we propose a feasible primal-dual path-following algorithm for convex quadratic programs.At each interior-point iteration the algorithm uses a full-Newton step and a suitable proximity measure for tracing approximately the central path.We show that the short-step algorithm has the best known iteration bound,namely O( √ n log (n+1) ).
متن کاملA primal-dual method for conic constrained distributed optimization problems
We consider cooperative multi-agent consensus optimization problems over an undirected network of agents, where only those agents connected by an edge can directly communicate. The objective is to minimize the sum of agentspecific composite convex functions over agent-specific private conic constraint sets; hence, the optimal consensus decision should lie in the intersection of these private se...
متن کاملA primal-dual interior-point method for linear optimization based on a new proximity function
In this paper we present a generic primal-dual interior-point algorithm for linear optimization in which the search direction depends on a univariate kernel function which is also used as proximity measure in the analysis of the algorithm. We present some powerful tools for the analysis of the algorithm under the assumption that the kernel function satisfies three easy to check and mild conditi...
متن کاملA weighted full-Newton step primal-dual interior point algorithm for convex quadratic optimization
In this paper, a new weighted short-step primal-dual interior point algorithm for convex quadratic optimization (CQO) problems is presented. The algorithm uses at each interior point iteration only full-Newton steps and the strategy of the central path to obtain an ε-approximate solution of CQO. This algorithm yields the best currently wellknown theoretical iteration bound, namely, O( √ n log ε...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Programming
سال: 2003
ISSN: 0025-5610,1436-4646
DOI: 10.1007/s10107-002-0349-3