Results 11 to 20 of about 15,567,526 (268)
Adapting the interior point method for the solution of linear programs on high performance computers [PDF]
, 1991 In this paper we describe a unified algorithmic framework for the interior point method (IPM) of solving Linear Programs (LPs) which allows us to adapt it over a range of high performance computer architectures. We set out the reasons as to why IPM makes
Levkovitz, R, Mitra, G, Anderson, J
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Experimental investigations in combining primal dual interior point method and simplex based LP solvers [PDF]
, 1993 The use of a primal dual interior point method (PD) based optimizer as a robust linear programming (LP) solver is now well established. Instead of replacing the sparse simplex algorithm (SSX), the PD is increasingly seen as complementing it. The progress
Levkovitz, R +5 more
core +6 more sources
Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers [PDF]
, 1990 In this paper we describe a unified scheme for implementing an interior point algorithm (IPM) over a range of computer architectures. In the inner iteration of the IPM a search direction is computed using Newton's method.
Levkovitz, R +3 more
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Convergence analysis of an Inexact Infeasible Interior Point method for Semidefinite Programming [PDF]
, 2004 In this paper we present an extension to SDP of the well known infeasible Interior Point method for linear programming of Kojima,Megiddo and Mizuno (A primal-dual infeasible-interior-point algorithm for Linear Programming, Math. Progr., 1993).
Pieraccini, Sandra, Bellavia, S
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The Symbolic Interior Point Method
Proceedings of the AAAI Conference on Artificial Intelligence, 2017 Numerical optimization is arguably the most prominent computational framework in machine learning and AI. It can be seen as an assembly language for hard combinatorial problems ranging from classification and regression in learning, to computing optimal policies and equilibria in decision theory, to entropy minimization in information ...
Mladenov, Martin +2 more
openaire +5 more sources
A New Hybrid Preconditioner for the Interior Point Method
Trends in Computational and Applied Mathematics, 2019 This study aims to improve the computation of the search direction in the primal-dual Interior Point Method through preconditioned iterative methods. It is about a hybrid approach that combines the Controlled Cholesky Factorization preconditioner and ...
Manolo Rodriguez Heredia +2 more
doaj +1 more source
Komputasi Aliran Daya Optimal Sistem Tenaga Skala Besar dengan Metode Primal Dual Interior Point
Jurnal Rekayasa Elektrika, 2016 This paper focuses on the use of Primal Dual Interior Point method in the analysis of optimal power flow. Optimal power flow analysis with Primal Dual Interior Point method then compared with Linear Programming Method using Matpower program.
Syafii Syafii, Ikhwannul Kadri Masrul
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Journal of Computational and Applied Mathematics, 2000 The simplex method starts from a basic feasible solution and moves along the boundary of the feasible region until an optimum is reached. At each step, the algorithm brings only one new variable into the basic set, regardless of the total number of variables.
Potra, Florian A., Wright, Stephen J.
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Experimental investigation of an interior search method within a simple framework [PDF]
, 1986 A steepest gradient method for solving Linear Programming (LP) problems, followed by a procedure for purifying a non-basic solution to an improved extreme point solution have been embedded within an otherwise simplex based optimiser.
Mitra, G, Yadeger, J, Tamiz, M
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A new non-monotonic infeasible simplex-type algorithm for Linear Programming [PDF]
PeerJ Computer Science, 2020 This paper presents a new simplex-type algorithm for Linear Programming with the following two main characteristics: (i) the algorithm computes basic solutions which are neither primal or dual feasible, nor monotonically improving and (ii) the sequence ...
Charalampos P. Triantafyllidis +1 more
doaj +2 more sources