Title : ( A Projection RNN For Non-Convex Optimization Problems )
Authors: Amin Mansoori , Sohrab Effati , ,
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Abstract
The present scientific attempt is devoted to investigating the nonconvex optimization problems (NCOPs) utilizing the concepts of projection Recurrent Neural Networks (RNN)s. For this purpose, the original problem is reformulated into a m-th power form. Then, the Karush–Kuhn–Tucker (KKT) optimality conditions are provided. The KKT conditions are used to propose the RNN model. An illustrated example is given.
Keywords
, nonconvex optimization problem, RNN model
@inproceedings{paperid:1078133,
author = {امین منصوری and Effati, Sohrab and , },
title = {A Projection RNN For Non-Convex Optimization Problems},
booktitle = {The Third National Seminar on Control and Optimization},
year = {2019},
location = {سبزوار, IRAN},
keywords = {nonconvex optimization problem-RNN model},
}
%0 Conference Proceedings
%T A Projection RNN For Non-Convex Optimization Problems
%A امین منصوری
%A Effati, Sohrab
%A ,
%J The Third National Seminar on Control and Optimization
%D 2019
