Homotopy Methods for Convex Optimization

التفاصيل البيبلوغرافية
العنوان: Homotopy Methods for Convex Optimization
المؤلفون: Klingler, Andreas, Netzer, Tim
سنة النشر: 2024
المجموعة: Computer Science
Mathematics
مصطلحات موضوعية: Mathematics - Optimization and Control, Mathematics - Algebraic Geometry, Mathematics - Numerical Analysis
الوصف: Convex optimization encompasses a wide range of optimization problems, containing many efficiently solvable subclasses. Interior point methods are currently the state-of-the-art approach for solving such problems, particularly effective for classes like semidefinite programming, quadratic programming, and geometric programming. However, their success hinges on the construction of self-concordant barrier functions for the feasible sets. In this work, we introduce an alternative method for tackling convex optimization problems, employing a homotopy. With this technique, the feasible set of a trivial optimization problem is continuously transformed into the target one, while tracking the solutions. We conduct an analysis of this approach, focusing on its application to semidefinite programs, hyperbolic programs, and convex optimization problems with a single convexity constraint. Moreover, we demonstrate that our approach numerically outperforms state-of-the-art methods in several interesting cases.
Comment: 29 pages, 10 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2403.02095
رقم الأكسشن: edsarx.2403.02095
قاعدة البيانات: arXiv