Biofilm Algorithm for Global Numerical Optimization
R. Vasundhara Devi1, S. Siva Sathya2
1R. Vasundhara Devi, PhD. Degree, Department of Computer Science, Pondicherry University, (Pondicherry), India.
2Dr. S. Siva Sathya, Associate Professor, Department of Computer Science, Pondicherry University, (Pondicherry), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 23-29 | Volume-8 Issue-5, March 2019 | Retrieval Number: D2761028419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Swarm intelligence algorithms are based on the behavior and intelligence of living organisms that exist in nature. Amidst living organisms, Bacteria is a micro-organism that exhibit intelligent behavior by the development of biofilms to overcome harsh and adverse environment such as antibiotics and other bacteria. This survival behavior of bacteria forms the basis for the design of Biofilm (Bifi) algorithm in this paper. Biofilm algorithm uses three important characteristics of biofilm forming bacteria viz., conjugation, transformation and quorum sensing for solving real-world optimization problems. Biofilm algorithm is applied to global numerical benchmark test functions and compared with known state-of-the-art optimization algorithms.
Keyword: Bacteria Behavior, Biofilm, Swarm Intelligence Algorithm, Single Objective Optimization.
Scope of the Article: Data Analytics Modelling and Algorithms