An efficient neural network for solving convex optimization problems with a nonlinear complementarity problem function
Sign Up to like & getrecommendations! Published in 2020 at "Soft Computing"
DOI: 10.1007/s00500-019-04189-8
Abstract: In this paper, we present a one-layer recurrent neural network (NN) for solving convex optimization problems by using the Mangasarian and Solodov (MS) implicit Lagrangian function. In this paper by using Krush–Kuhn–Tucker conditions and MS… read more here.
Keywords: convex optimization; neural network; problem; optimization problems ... See more keywords
FOM – a MATLAB toolbox of first-order methods for solving convex optimization problems
Sign Up to like & getrecommendations! Published in 2019 at "Optimization Methods and Software"
DOI: 10.1080/10556788.2018.1437159
Abstract: This paper presents the FOM MATLAB toolbox for solving convex optimization problems using first-order methods. The diverse features of the eight solvers included in the package are illustrated through a collection of examples of different… read more here.
Keywords: optimization problems; convex optimization; optimization; solving convex ... See more keywords
The Combination Projection Method for Solving Convex Feasibility Problems
Sign Up to like & getrecommendations! Published in 2018 at "Mathematics"
DOI: 10.3390/math6110249
Abstract: In this paper, we propose a new method, which is called the combination projection method (CPM), for solving the convex feasibility problem (CFP) of finding some x * ∈ C : = ∩ i =… read more here.
Keywords: convex feasibility; method; combination projection; projection ... See more keywords