By Topic

A solution of combinatorial optimization problem by uniting genetic algorithms with Hopfield's model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
H. Shirai ; Dept. of Electr. & Electron. Syst., Osaka Prefecture Univ., Sakai, Japan ; A. Ishigame ; S. Kawamoto ; T. Taniguchi

It is important to solve a combinatorial optimization problem because of its utility. In this paper, the authors propose a method of solving combinatorial optimization problems by uniting genetic algorithms (GAs) with Hopfield's model (Hp model). The authors also apply it to the traveling salesman problem (TSP). GAs are global search algorithms. On the other hand, in the Hp model the range of a search is in the neighborhood of the initial point. Then the Hp model is local search algorithm. By using these natures that make up for defects of each other, the authors unite GAs with the Hp model. Then the authors can overcome some difficulties, such as coding and crossover in GAs and setting up the initial point and parameter in the Hp model. The availability of the authors' proposed approach is verified by simulations

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:7 )

Date of Conference:

27 Jun-2 Jul 1994