نتایج جستجو برای: primal rings

تعداد نتایج: 53952  

2015
Ashish Cherukuri Enrique Mallada Jorge Cortés

This paper characterizes the asymptotic convergence properties of the primal-dual dynamics to the solutions of a constrained concave optimization problem using classical notions from stability analysis. We motivate our study by providing an example which rules out the possibility of employing the invariance principle for hybrid automata to analyze the asymptotic convergence. We understand the s...

2015
Ryan Tibshirani Jayanth Krishna Mogali Hsu-Chieh Hu

The Lagrange dual function is: g(u, v) = min x L(x, u, v) The corresponding dual problem is: maxu,v g(u, v) subject to u ≥ 0 The Lagrange dual function can be viewd as a pointwise maximization of some affine functions so it is always concave. The dual problem is always convex even if the primal problem is not convex. For any primal problem and dual problem, the weak duality always holds: f∗ ≥ g...

Journal: :Fuzzy Sets and Systems 2002
Yihua Zhong Yong Shi

This paper presents a parametric approach for duality in fuzzy multi-criteria and multi-constraint level linear programming (MCLP) which extends fuzzy linear programming approaches. First, the MC-simplex method is used to solve the crisp prima–dual MCLP pair and then, through these crisp formulations, separate membership functions are constructed for fuzzy primal and dual program by considering...

Journal: :Comp. Opt. and Appl. 2008
Damián R. Fernández Mikhail V. Solodov

We consider the class of quadratically-constrained quadratic-programming methods in the framework extended from optimization to more general variational problems. Previously, in the optimization case, Anitescu (SIAM J. Optim. 12, 949–978, 2002) showed superlinear convergence of the primal sequence under the Mangasarian-Fromovitz constraint qualification and the quadratic growth condition. Quadr...

2015
Mariette Annergren Sina Khoshfetrat Pakazad Anders Hansson Bo Wahlberg

In this paper we propose an efficient distributed algorithm for solving loosely coupled convex optimization problems. The algorithm is based on a primal-dual interior-point method in which we use the alternating direction method of multipliers (ADMM) to compute the primal-dual directions at each iteration of the method. This enables us to join the exceptional convergence properties of primal-du...

2011
Pooran Memari Patrick Mullen Mathieu Desbrun

Motivated by practical numerical issues in a number of modeling and simulation problems, we introduce the notion of a compatible dual complex to a primal triangulation, such that a simplicial mesh and its compatible dual complex (made out of convex cells) form what we call a primal-dual triangulation. Using algebraic and computational geometry results, we show that compatible dual complexes exi...

2017
Jialei Wang Lin Xiao

We consider empirical risk minimization of linear predictors with convex loss functions. Such problems can be reformulated as convex-concave saddle point problems, and thus are well suitable for primal-dual first-order algorithms. However, primal-dual algorithms often require explicit strongly convex regularization in order to obtain fast linear convergence, and the required dual proximal mappi...

Journal: :Math. Program. 1993
Masakazu Kojima Nimrod Megiddo Shinji Mizuno

This paper proposes two sets of rules Rule G and Rule P for controlling step lengths in a generic primal dual interior point method for solving the linear program ming problem in standard form and its dual Theoretically Rule G ensures the global convergence while Rule P which is a special case of Rule G ensures the O nL iteration polynomial time computational complexity Both rules depend only o...

Journal: :Intelligent Automation & Soft Computing 2009
Weirong Liu Jianqiang Yi Dongbin Zhao

Based on optimal theory, Kelly model realizes the bandwidth allocation on network with proportional fairness and has asymptotical stability. However, the primal algorithm of Kelly model leads to the packet accumulation in the queue of the bottleneck link. By using heuristic fuzzy rules, this paper designs a fuzzy controller to adjust the additive increase parameter of the primal algorithm dynam...

2008
Tim Carnes David B. Shmoys

Primal-dual algorithms have played an integral role in recent developments in approximation algorithms, and yet there has been little work on these algorithms in the context of LP relaxations that have been strengthened by the addition of more sophisticated valid inequalities. We introduce primal-dual schema based on the LP relaxations devised by Carr, Fleischer, Leung & Phillips for the minimu...

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