A subgradient-based convex approximations method for DC programming and its applications
نویسندگان
چکیده
منابع مشابه
A New Distributed DC-Programming Method and its Applications
We propose a novel decomposition framework for the distributed optimization of Difference Convex (DC)-type nonseparable sum-utility functions subject to coupling convex constraints. A major contribution of the paper is to develop for the first time a class of (inexact) best-response-like algorithms with provable convergence, where a suitably convexified version of the original DC program is ite...
متن کاملA new approach to fuzzy quantities ordering based on distance method and its applications for solving fuzzy linear programming
Many ranking methods have been proposed so far. However, there is yet no method that can always give a satisfactory solution to every situation; some are counterintuitive, not discriminating; some use only the local information of fuzzy values; some produce different ranking for the same situation. For overcoming the above problems, we propose a new method for ranking fuzzy quantities based on ...
متن کاملA Method for Solving Convex Quadratic Programming Problems Based on Differential-algebraic equations
In this paper, a new model based on differential-algebraic equations(DAEs) for solving convex quadratic programming(CQP) problems is proposed. It is proved that the new approach is guaranteed to generate optimal solutions for this class of optimization problems. This paper also shows that the conventional interior point methods for solving (CQP) problems can be viewed as a special case of the n...
متن کاملTechnical Report Subgradient Optimization for Convex Multiparametric Programming
In this paper we develop a subgradient optimization methodology for convex multiparametric nonlinear programs. We define a parametric subgradient, extend some classical optimization results to the multiparametric case, and design a subgradient algorithm that is shown to converge under traditional conditions. We use this algorithm to solve two illustrative example problems and demonstrate its ac...
متن کاملErgodic, primal convergence in dual subgradient schemes for convex programming
Lagrangean dualization and subgradient optimization techniques are frequently used within the field of computational optimization for finding approximate solutions to large, structured optimization problems. The dual subgradient scheme does not automatically produce primal feasible solutions; there is an abundance of techniques for computing such solutions (via penalty functions, tangential app...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Industrial and Management Optimization
سال: 2016
ISSN: 1547-5816
DOI: 10.3934/jimo.2016.12.1349