Menu
Publications
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
COMPARATIVE STUDY OF TABU-MACHINE AND HOPFIELD NEURAL NETWORKS APPLICATION TO SOLVE DISCRETE OPTIMIZATION PROBLEMS FROM DISTRIBUTED DATABASES DOMAIN
Read the full article
';
Abstract
We propose a new neural networks approach based on tabu-search to solve discrete optimization problems arising during the synthesis of optimal distributed database logical structures. The solutions with a quality on average greater by 3.8% than quality of the solutions, received with help of Hopfield networks, have been obtained. Thanks to optimization of Tabu-machine the operating time of data decomposition algorithm has been lowered in compare with an initial version of tabu-algorithm (on average more than twice) as well as with neural networks algorithm based on Hopfield networks (on average on 36%). In the course of the research the investigation of Tabu-machine parameters space has been carried out.
Keywords:
tabu search, neural networks, genetic algorithms, discrete optimization problems, distributed databases
