primal-dual interior-point algorithm
Large update interior point algorithm for P∗ linear complementarity problem
... an interior point algorithm and each barrier function is determined by its univariate kernel ...large-update primal-dual interior point algorithm for solving P ∗ ...
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New complexity analysis for primal-dual interior-point methods for self-scaled optimization problems
... long-step primal-dual interior-point algorithm for the optimization problem of the minimization of a linear function on a feasible set obtained as the intersection of an affine subspace ...
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INTERIOR-POINT METHODS FOR $P_{*}(\kappa)$-LINEAR COMPLEMENTARITY PROBLEM BASED ON GENERALIZED TRIGONOMETRIC BARRIER FUNCTION
... The primal-dual IP M for linear optimization (LO) problems was first in- troduced in [11, 14] and extended to various class of problems, ...the algorithm for LO problem independently, and since then ...
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Primal dual interior point QP free algorithm for nonlinear constrained optimization
... PTH algorithm may be insta- ble. Furthermore, the initial point must lie on the strict interior of the feasible set, and an additional assumption that ‘the number of stationary points is finite’ is ...
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Interior-proximal primal-dual methods
... proximal point methods for a class of saddle point problems, where the preconditioner decouples the overall proximal point method into an al- ternating primal–dual ...the dual ...
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A superlinearly convergent SSDP algorithm for nonlinear semidefinite programming
... fixed point problems [1–3], can be reformulated as convex ...[7–12], primal-dual interior point method [13, 14], and se- quential semidefinite programming (SSDP) method ...
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Generation Fuel Cost Minimization of Power Grid Using Primal Dual Interior Point OPF (Optimal Power Flow) Method
... scaling algorithm for linear programming proposed by ...Karmarkar’s algorithm is significantly different from Dantzig’s simplex ...Karmarkar’s interior point rarely visits too many extreme ...
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Kernel function based primal dual interior point methods for convex quadratic optimization over symmetric cone
... The paper generalizes results obtained in the following papers, [] where Bai et al. con- sider kernel-based primal-dual IPMs for LO, and [, , ] and [] where Bai et al., El Ghami et al., Wang et al. ...
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Nonlinear convex optimisation problems in the smart grid
... the primal-dual interior-point method (IPM) ...The primal-dual IPM is a general algorithm to solve nonlinear and convex optimisation problems, and therefore does not ...
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An Algorithm for NonparametricE stimation of A M ultivariateM ixing Distribution with Applications to P opulationP harmacokinetics
... a Primal-Dual Interior-Point method; the location of the support points is found by an Adaptive Grid ...Our algorithm has been successfully applied in hundreds of published ...
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State Estimation of the Tanzanian Power System Network Using Non-Quadratic Criterion and MATLAB Environment
... fast algorithm for the weighted least absolute value (WLAV) state estimation using simplex ...using interior point method is described in the work of Clements et al ...of interior point ...
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An Improved Affine Scaling Interior Point Algorithm for Linear Programming
... of interior point meth- ...suggests, interior point methods approach an optimal point (which is known to be on the boundary of the feasible set) through a sequence of interior ...
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An interior approximal method for solving pseudomonotone equilibrium problems
... an interior approximal method for solving equilibrium problems for pseudomonotone bifunctions without Lipschitz-type continuity on ...special interior proximal function, which replaces the usual quadratic ...
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Laplacian Support Vector Machines Trained in the Primal
... All presented results has been obtained by averaging them on different splits of the available data. In particular, a 4-fold cross-validation has been performed, randomizing the fold generation process for 3 times, for a ...
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Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
... convex dual of either the log-linear or max- margin objective function; the dual in both the log-linear and max-margin cases corresponds to minimizing a convex function with simplex ...the algorithm, ...
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On the implementation of a primal-dual algorithm for second order time-dependent Mean Field Games with local couplings
... The article is organized as follows. In section 2 we introduce some standard notation and we recall the finite difference scheme for (MFG) introduced in [3]. The variational interpretation of this finite difference ...
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A Primal-Dual Convergence Analysis of Boosting
... Section 5 will also reveal another structure: there is a subset of the training set, the hard core, which is the maximal support of any distribution upon which every weak learner and the training labels are uncorrelated. ...
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Dual and Partial Primal Solution for Solving Linear Sum Feasible Fuzzy Assignment Problem
... We proposed dual and primal partial feasible fuzzy assignment problem. Let ‘n’ number of jobs is performed by ‘m’ number of persons, where the costs coefficient is depend on -Trapezoidal fuzzy numbers. ...
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Optimal Adjustment Algorithm for p Coordinates and The Starting Point in Interior Point Methods
... adjustment algorithm for p coordinates is a generalization of the optimal pair adjustment algorithm for linear programming, which in turn is based on von Neumann’s ...the interior point ...
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On the Primal Dual Method of Multipliers and its Applications
... ADMM algorithm to remove the aggregation step in the dual update [138, 64] in order to make the al- gorithm more suited to distributed network based ...as dual gradient ascent decomposition and dif- ...
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