By Topic

Hybrid systems optimization using genetic algorithms

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
$31 $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

3 Author(s)
Jimin Tian ; Inst. of Syst. Eng., Tsinghua Univ., Beijing, China ; Jingwei Huang ; Chunjun Zhao

In this paper, a location optimization model is proposed and a hybrid modeling methodology is discussed. Then, a non-standard real-coded genetic algorithm is deployed to optimize this model. A multi-objective fitness function is also considered during the optimization process. This model and the corresponding optimization method are implemented in a master planning project in Guilin City in South China, and a satisfactory result is obtained

Published in:

Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on  (Volume:1 )

Date of Conference:

28-31 Oct 1997