Universiti Teknologi Malaysia Institutional Repository

The improved genetic algorithm for assignment problems

Cheshmehgaz, Hossein Rajabalipour and Haron, Habibollah and Jambak, Muhammad Ikhwan (2009) The improved genetic algorithm for assignment problems. In: 2009 International Conference on Signal Processing Systems, ICSPS 2009. Institute of Electrical and Electronics Engineers, New York, 187 -191. ISBN 978-076953654-5

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1109/ICSPS.2009.26


In this paper, we describe a new mechanism of cellular selection as an improved Genetic Algorithm for some optimization problems like Cellular Channel assignment which have multi feasible/optimum solution per one case. Considering the problems and the nature of relationship among individuals in population, we use 2-Dimention Cellular Automata in order to place the individuals onto its cells to make the locality and neighborhood on Hamming distance basis. This idea as 2D Cellular Automata Hamming GA has introduced locality in Genetic Algorithms and global knowledge for their selection process on Cells of 2D Cellular Automata. The selection based on 2D Cellular Automata can ensure maintaining population diversity and fast convergence in the genetic search. The cellular selection of individuals is controlled based on the structure of cellular automata, to prevent the fast population diversity loss and improve the convergence performance during the genetic search.

Item Type:Book Section
Additional Information:2009 International Conference on Signal Processing Systems, ICSPS 2009; Singapore; 15 May 2009 through 17 May 2009
Uncontrolled Keywords:cellular automata, genetic algorithms, NP-hard multi solutions problems, optimization
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:13142
Deposited By: Liza Porijo
Deposited On:19 Jul 2011 09:30
Last Modified:19 Jul 2011 09:30

Repository Staff Only: item control page