Coupling of Optimization Algorithms Based on Swarm Intelligence: An Application for Control of Heroin Addiction Epidemic

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Author(s): Kamalanand Krishnamurthy (Anna University, India)and Mannar Jawahar Ponnuswamy (Anna University, India)
Copyright: 2018
Pages: 24
Source title: Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems
Source Author(s)/Editor(s): Utku Kose (Suleyman Demirel University, Turkey), Gur Emre Guraksin (Afyon Kocatepe University, Turkey)and Omer Deperlioglu (Afyon Kocatepe University, Turkey)
DOI: 10.4018/978-1-5225-4769-3.ch002

Keywords: Medical Engineering / Medical Information Science Reference / Medicine & Healthcare

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Abstract

Swarm intelligence is a branch of computational intelligence where algorithms are developed based on the biological examples of swarming and flocking phenomena of social organisms such as a flock of birds. Such algorithms have been widely utilized for solving computationally complex problems in fields of biomedical engineering and sociology. In this chapter, two different swarm intelligence algorithms, namely the jumping frogs optimization (JFO) and bacterial foraging optimization (BFO), are explained in detail. Further, a synergetic algorithm, namely the coupled bacterial foraging/jumping frogs optimization algorithm (BFJFO), is described and utilized as a tool for control of the heroin epidemic problem.

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Coupling of Optimization Algorithms Based on Swarm Intelligence: An Application for Control of Heroin Addiction Epidemic

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