Firefly algorithm

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Scientific Research Group in Egypt (SRGE)
Swarm Intelligence (6)
Firefly algorithm
Dr. Ahmed Fouad Ali
Suez Canal University,
Dept. of Computer Science, Faculty of Computers and informatics
Member of the Scientific Research Group in Egypt

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LOGO Scientific Research Group in Egypt
www.egyptscience.net

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LOGO Outline
1.Firefly algorithm (History and main idea)
4. The basic steps of the firefly Algorithm
3. Characteristics of firefly algorithm
5. Application of the firefly Algorithm
2. Behavior of fireflies
6. References

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LOGO Firefly algorithm (History and main idea)
Firefly Algorithm (FA) was first developed
by Xin-She Yang in late 2007, which was
based on the flashing patterns and behavior of
fireflies
Firefly algorithm is a metaheuristic
population based method.

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LOGO Behavior of fireflies
•The sky filled with the light of fireflies is a
marvelous sight in the summer in the
moderately temperature regions.
•There are near to two thousand firefly
species, and most of them produce short and
rhythmic flashes.
•The pattern observed for these flashes is
unique for most of the times for a specific
species.
•Females of a species respond to individual
pattern of the male of the same species.

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LOGO Characteristics of firefly algorithm
• Fireflies are unisex so that one firefly will be
attracted to other fireflies regardless of their sex.
• The attractiveness is proportional to the
brightness, and they both decrease as their
distance increases.
•For any two flashing fireflies, the less brighter
one will move towards the brighter one.
•If there is no brighter one than a particular
firefly, it will move randomly.
•The brightness of a firefly is determined by the
landscape of the objective function.

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The light intensity I (r) varies following the
inverse square law
Where I0 represents the light intensity at the
source.
The combined effect the inverse square law
and absorption can be approximated using the
following Gaussian form:
The basic steps of the firefly Algorithm
(attractiveness )

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As a firefly’s attractiveness is proportional to
the light intensity seen by adjacent fireflies, the
attractiveness function of the firefly is
established by:
Where β0 is the firefly attractiveness value at r =
0 and γ is the media light absorption
coefficient.
The basic steps of the firefly Algorithm
(attractiveness )

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Fireflies movement is based on the principles of
attractiveness: when firefly j is more attractive
than firefly i the movement is determined by the
following equation:
The basic steps of the firefly Algorithm
(movement )
where k =1,2,...,D (D is dimension of
problem), α and Sk are the scaling parameters
and randik rand is random number between 0
and 1.

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LOGO
Distance rij between fireflies i and j is obtained
by Cartesian distance form by:
The basic steps of the firefly Algorithm (distanc
)

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•If β0 = 0, it becomes a simple random walk.
•On the other hand, if γ = 0, it reduces to a
variant of particle swarm optimization
The basic steps of the firefly Algorithm (special
case )

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The basic steps of the firefly Algorithm
(algorithm)

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•Digital Image Compression and Image
Processing
•Feature selection and fault detection
•Antenna Design
•Structural Design
•Scheduling
•Semantic Web Composition
•Chemical Phase equilibrium
•Clustering
•Dynamic Problems
•Rigid Image Registration Problems
Application of the firefly Algorithm

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LOGO References
• X. S. Yang, “Nature-Inspired Metaheuristic Algorithms”,
Luniver Press, 2008.
•Xin-She Yang, Firefly Algorithms for Multimodal Optimization,
2010
• Xin-She Yang, Comparative Study of Firefly Algorithm and
Particle Swarm Optimization for Noisy Non-Linear
Optimization Problems, 2010, ISBN: 1-905986-28-9

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Thank you
http://www.egyptscience.net
Ahmed_fouad@ci.suez.edu.eg