Adapting the interior point method for the solution of linear programs on high performance computers [PDF]
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 +5 more
core +8 more sources
Experimental investigations in combining primal dual interior point method and simplex based LP solvers [PDF]
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 +7 more sources
Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers [PDF]
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
core +7 more sources
Convergence analysis of an Inexact Infeasible Interior Point method for Semidefinite Programming [PDF]
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 +2 more
core +1 more source
A New Hybrid Preconditioner for the Interior Point Method
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
The Symbolic Interior Point Method
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
Komputasi Aliran Daya Optimal Sistem Tenaga Skala Besar dengan Metode Primal Dual Interior Point
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
doaj +1 more source
A new non-monotonic infeasible simplex-type algorithm for Linear Programming [PDF]
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
Optimal Load Shedding in Deregulated System and Consideration of Effective Factors by Using a Predictor-Corrector Interior-Point Method (IPM) [PDF]
In this paper, intifially an introduction is presented about Electric Power market in deregulated system and load shedding by interior-point method in these systems. Then, predictor-corrector of IPM is considered and by consideration of the IEEE 6 busbar
Mojtaba Afshari, Saeed Abazari
doaj
Matrix Structure Driven Interior Point Method for Quadrotor Real-Time Trajectory Planning
Sequential convex programming (SCP) has been recently employed in various trajectory planning problems, including entry flight, planetary landing, and aircraft formation.
Guangtong Xu +3 more
doaj +1 more source

