A Numerical Implementation of an Interior Point Methods for Linear Programming Based on a New Kernel Function

DOI10.1007/978-3-319-18161-5_30zbMath1370.90139OpenAlexW939534964MaRDI QIDQ5356999

Adnan Yassine, Djamel Benterki, Mousaab Bouafia

Publication date: 12 September 2017

Published in: Advances in Intelligent Systems and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-18161-5_30

zbMATH Keywords

kernel functioninterior point methodslinear optimizationcomplexity bound

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Abstract computational complexity for mathematical programming problems (90C60) Linear programming (90C05) Interior-point methods (90C51)

Cites Work

• Interior-point methods for linear optimization based on a kernel function with a trigonometric barrier term
• An interior-point algorithm for linear optimization based on a new barrier function
• A new polynomial-time algorithm for linear programming
• A polynomial-time algorithm for linear optimization based on a new class of kernel functions
• Self-regular functions and new search directions for linear and semidefinite optimization
• A new proximity function generating the best known iteration bounds for both large-update and small-update interior-point methods
• Generic Primal-dual Interior Point Methods Based on a New Kernel Function
• Path-Following Methods for Linear Programming
• A New Efficient Large-Update Primal-Dual Interior-Point Method Based on a Finite Barrier
• A polynomial-time algorithm for linear optimization based on a new simple kernel function
• A Comparative Study of Kernel Functions for Primal-Dual Interior-Point Algorithms in Linear Optimization
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