
A Full-Newton Step Interior Point Method for Fractional Programming Problem Involving Second Order Cone Constraint
Author(s) -
Mansour Saraj,
Ali Sadeghi,
Nezam Mahdavi–Amiri
Publication year - 2021
Publication title -
pakistan journal of statistics and operation research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.354
H-Index - 15
eISSN - 2220-5810
pISSN - 1816-2711
DOI - 10.18187/pjsor.v17i2.2431
Subject(s) - mathematics , interior point method , fractional programming , cone (formal languages) , logarithm , second order cone programming , mathematical optimization , function (biology) , order (exchange) , constraint (computer aided design) , set (abstract data type) , point (geometry) , algorithm , mathematical analysis , nonlinear programming , geometry , computer science , physics , finance , quantum mechanics , nonlinear system , convex optimization , regular polygon , evolutionary biology , economics , biology , programming language
Some efficient interior-point methods (IPMs) are based on using a self-concordant barrier function related to the feasibility set of the underlying problem.Here, we use IPMs for solving fractional programming problems involving second order cone constraints. We propose a logarithmic barrier function to show the self concordant property and present an algorithm to compute $\varepsilon-$solution of a fractional programming problem. Finally, we provide a numerical example to illustrate the approach.