This paper is published in Volume-7, Issue-3, 2021
Area
Engineering Optimization
Author
Mohd Aquib
Org/Univ
Indian Institute of Technology, Kanpur, Uttar Pradesh, India
Pub. Date
19 May, 2021
Paper ID
V7I3-1347
Publisher
Keywords
Interior Point Methods, KKT Condition, Kernel Function

Citationsacebook

IEEE
Mohd Aquib. A comparative analysis of interior-point methods in convex optimization, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Mohd Aquib (2021). A comparative analysis of interior-point methods in convex optimization. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.

MLA
Mohd Aquib. "A comparative analysis of interior-point methods in convex optimization." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.

Abstract

Interior point methods or sometimes called Barrier methods are a class of optimization algorithms that are useful in solving inequality constrained linear or nonlinear programming problems. The optimization problem with inequality constraint is solved by using the Newtons method by converting it into series of equality constraints or KKT conditions. This paper presents the comparative study of the classical logarithmic barrier method and the primal-dual interior-point method along with their convergence analysis. A kernel function-based interior point method for second-order cone problems is also examined. The computational complexity of the algorithms is also discussed along with the implementation issues.
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