By Topic

An Adaptive Multimeme Algorithm for Designing HIV Multidrug Therapies

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

4 Author(s)
Neri, F. ; Y.-S. Ong is with the School of Computer Engineering, Nanyang Technological University, Blk N4, 2b-39, Nanyang Avenue, Singapore 639798 ; Toivanen Jari ; Cascella L. ; Yew-Soon Ong

This paper proposes a period representation for modelling the multidrug HIV therapies and an Adaptive Multimeme Algorithm (AMmA) for designing the optimal therapy. The period representation offers benefits in terms of flexibility and reduction in dimensionality compared to the binary representation. The AMmA is a memetic algorithm which employs a list of three local searchers adaptively activated by an evolutionary framework. These local searchers, having different features according to the exploration logic and the pivot rule, have the role of exploring the decision space from different and complementary perspectives and, thus, assisting the standard evolutionary operators in the optimization process. Furthermore, the AMmA makes use of an adaptation which dynamically sets the algorithmic parameters in order to prevent the stagnation and premature convergence. The numerical results demonstrate that the application of the proposed algorithm leads to very efficient medication schedules which quickly stimulate a strong immune response to HIV. The earlier termination of the medication schedule leads to lesser unpleasant side effects for the patient due to strong anti-retroviral therapy. A numerical comparison shows that the AMmA is more efficient than three popular metaheuristcs. Finally a statistical test based on the calculation of the tolerance interval confirms the superiority of the AMmA compared to the other methods, for the problem under study.

Published in:

Computational Biology and Bioinformatics, IEEE/ACM Transactions on  (Volume:PP ,  Issue: 99 )