An interior-point based subgradient method for nondifferentiable convex optimization

1998 ◽  
Vol 10 (2) ◽  
pp. 197-215
Author(s):  
J. B. G. Frenk ◽  
J. F. Sturm ◽  
S. Zhang
2017 ◽  
Vol 50 (1) ◽  
pp. 15319-15324 ◽  
Author(s):  
Yuichi Kajiyama ◽  
Naoki Hayashi ◽  
Shigemasa Takai

2014 ◽  
Vol 15 (3) ◽  
pp. 253-261 ◽  
Author(s):  
S. Sivasubramani ◽  
Md. Samar Ahmad

Abstract This paper proposes a new hybrid algorithm combining harmony search (HS) algorithm and interior point method (IPM) for economic dispatch (ED) problem with valve-point effect. ED problem with valve-point effect is modeled as a non-linear, constrained and non-convex optimization problem having several local minima. IPM is a best non-linear optimization method for convex optimization problems. Since ED problem with valve-point effect has multiple local minima, IPM results in a local optimum solution. In order to avoid IPM getting trapped in a local optimum, a new evolutionary algorithm HS, which is good in global exploration, has been combined. In the hybrid method, HS is used for global search and IPM for local search. The hybrid method has been tested on three different test systems to prove its effectiveness. Finally, the simulation results are also compared with other methods reported in the literature.


2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Sakineh Tahmasebzadeh ◽  
Hamidreza Navidi ◽  
Alaeddin Malek

This paper proposes three numerical algorithms based on Karmarkar’s interior point technique for solving nonlinear convex programming problems subject to linear constraints. The first algorithm uses the Karmarkar idea and linearization of the objective function. The second and third algorithms are modification of the first algorithm using the Schrijver and Malek-Naseri approaches, respectively. These three novel schemes are tested against the algorithm of Kebiche-Keraghel-Yassine (KKY). It is shown that these three novel algorithms are more efficient and converge to the correct optimal solution, while the KKY algorithm fails in some cases. Numerical results are given to illustrate the performance of the proposed algorithms.


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