A bio-inspired evolutionary algorithm: allostatic optimisation Online publication date: Wed, 18-May-2016
by Valentín Osuna-Enciso; Erik Cuevas; Diego Oliva; Humberto Sossa; Marco Pérez-Cisneros
International Journal of Bio-Inspired Computation (IJBIC), Vol. 8, No. 3, 2016
Abstract: Over the last decade, several bio-inspired algorithms have emerged for solving complex optimisation problems. Since the performance of these algorithms present a suboptimal behaviour, a tremendous amount of research has been devoted to find new and better optimisation methods. On the other hand, allostasis is a medical term recently coined which explains how the configuration of the internal state (IS) in different organs allows reaching stability when an unbalance condition is presented. In this paper, a novel biologically-inspired algorithm called allostatic optimisation (AO) is proposed for solving optimisation problems. In AO, individuals emulate the IS of different organs. In the approach, each individual is improved by using numerical operators based on the biological principles of the allostasis mechanism. The proposed method has been compared to other well-known optimisation algorithms. The results show good performance of the proposed method when searching for a global optimum of several benchmark functions.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Bio-Inspired Computation (IJBIC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com