کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
403964 677376 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A collective neurodynamic optimization approach to bound-constrained nonconvex optimization
ترجمه فارسی عنوان
رویکرد بهینه سازی جمعی نورودینامیکی بهینه سازی بدون محدودیت محدود
کلمات کلیدی
بهینه سازی نورو دینامیکی جمعی، شبکه عصبی مکرر، بهینه سازی غیرقانونی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

This paper presents a novel collective neurodynamic optimization method for solving nonconvex optimization problems with bound constraints. First, it is proved that a one-layer projection neural network has a property that its equilibria are in one-to-one correspondence with the Karush–Kuhn–Tucker points of the constrained optimization problem. Next, a collective neurodynamic optimization approach is developed by utilizing a group of recurrent neural networks in framework of particle swarm optimization by emulating the paradigm of brainstorming. Each recurrent neural network carries out precise constrained local search according to its own neurodynamic equations. By iteratively improving the solution quality of each recurrent neural network using the information of locally best known solution and globally best known solution, the group can obtain the global optimal solution to a nonconvex optimization problem. The advantages of the proposed collective neurodynamic optimization approach over evolutionary approaches lie in its constraint handling ability and real-time computational efficiency. The effectiveness and characteristics of the proposed approach are illustrated by using many multimodal benchmark functions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 55, July 2014, Pages 20–29
نویسندگان
, , ,