System Maintenance:
There may be intermittent impact on performance while updates are in progress. We apologize for the inconvenience.
By Topic

DNA Sequence Design for Direct-Proportional Length-Based DNA Computing: Particle Swarm Optimization vs Population Based Ant Colony Optimization

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

6 Author(s)
Yusof, Z.M. ; Fac. of Electr. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia ; Rahim, M.A.A. ; Nawawi, S.W. ; Khalil, K.
more authors

Generally, in DNA computing, the DNA sequences used for the computation should be critically designed in order to reduce error that could occur during computation. Previously, direct-proportional length-based DNA computing which involved DNA sequences with different lengths has been implemented to solve the shortest path problem. In this study, particle swarm optimization (PSO) and population-based ant colony optimization (P-ACO) are employed to design DNA sequences with different lengths and the results obtained are compared. Further comparison with the sequences generated by graph and generate-and-test methods is presented. The results show that P-ACO approach can generate relatively better DNA sequences in some objectives than PSO approach and the other methods. It can be concluded that the P-ACO algorithm can obtain relatively a better set of DNA sequences for DNA computing with length constraints.

Published in:

Computational Intelligence, Modelling and Simulation (CIMSiM), 2012 Fourth International Conference on

Date of Conference:

25-27 Sept. 2012