What is it about?
This paper proposes inexact subgradient methods to solve quasi-convex minimization problems leading to convergence results.
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Why is it important?
Quasi-convex minimization problems are important optimization problems that are not convex, but ``close" to being convex, and it is worthwhile to study methods to solve this class of problems, as this paper has done.
Perspectives
Quasi-convex minimization problems are interesting problems to study, and they have enough structure to get good results when we apply optimization algorithms to solve them.
Dr Chee Khian Sim
University of Portsmouth
Read the Original
This page is a summary of: Inexact subgradient methods for quasi-convex optimization problems, European Journal of Operational Research, January 2015, Elsevier,
DOI: 10.1016/j.ejor.2014.05.017.
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