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Department Of Computer Science Engineering
Seemanta Engineering College
Jharpokharia,Mayurbhanj,757086
Cuckoo Search Algorithm
Under the supervision of Er. Abhimanyu sahu
Sambhram Basu
Roll No:2016P43
Regd No:1601201095
November 1, 2019
1
presentation Outline
Introduction
Cuckoo search algorithm (History and main idea)
Behavior of Cuckoo breeding
Behavior of Cuckoo breeding (Cont.)
Characteristics of Cuckoo search
Characteristics of Cuckoo search (cont)
Levy Flights
Levy Flights (Cont.)
Cuckoo search Algorithm
Cuckoo search Algorithm (Cont)
Application of the CS Algorithm
References
Sambhram Basu | Cuckoo Search Algorithm
2
Introduction
In operations research, cuckoo search is an optimization
algorithm developed by Xin-she Yang and Suash Deb in
2009.[1][2] It was inspired by the obligate brood parasitism of
some cuckoo species by laying their eggs in the nests of other
host birds (of other species). Some host birds can engage direct
con鍖ict with the intruding cuckoos. For example, if a host bird
discovers the eggs are not their own, it will either throw these
alien eggs away or simply abandon its nest and build a new nest
elsewhere. Some cuckoo species such as the New World
brood-parasitic Tapera have evolved in such a way that female
parasitic cuckoos are often very specialized in the mimicry in
colors and pattern of the eggs of a few chosen host species.[3]
Cuckoo search idealized such breeding behavior, and thus can
be applied for various optimization problems.
Sambhram Basu | Cuckoo Search Algorithm
3
Cuckoo search algorithm (History and main idea)
A method of global
optimization based on the
behavior of cuckoos was
proposed by Yang Deb
(2009).
The original cuckoo search
(CS) algorithm is based on
the idea of the following :-
How cuckoos lay their eggs in
the host nests.
How, if not detected and
destroyed, the egg are
hatched to chicks by the
hosts.
How a search algorithm
based on such a scheme can
be used to 鍖nd the global
Figure: Yang Deb
Sambhram Basu | Cuckoo Search Algorithm
4
Behavior of Cuckoo breeding
The CS was inspired by the
obligate brood parasitism of
some cuckoo species by
laying their eggs in the nests
of host birds.
Some cuckoos have evolved
in such a way that female
parasitic cuckoos can imitate
the colors and patterns of the
eggs of a few chosen host
species.
This reduces the probability of
the eggs being abandoned
and, therefore, increases their
reproductivity .
Figure: 1
Sambhram Basu | Cuckoo Search Algorithm
5
Behavior of Cuckoo breeding (Cont.)
If host birds discover the eggs
are not their own, they will
either throw them away or
simply abandon their nests
and build new ones.
Parasitic cuckoos often
choose a nest where the host
bird just laid its own eggs.
In general, the cuckoo eggs
hatch slightly earlier than their
host eggs.
Figure: 2
Sambhram Basu | Cuckoo Search Algorithm
6
Once the 鍖rst cuckoo chick is
hatched, his 鍖rst instinct
action is to evict the host eggs
by blindly propelling the eggs
out of the nest.
This action results in
increasing the cuckoo chicks
share of food provided by its
host bird .
Moreover, studies show that a
cuckoo chick can imitate the
call of host chicks to gain
access to more feeding
opportunity. Figure: 3
Sambhram Basu | Cuckoo Search Algorithm
7
Characteristics of Cuckoo search
Each egg in a nest represents
a solution, and a cuckoo egg
represents a new solution.
The aim is to employ the new
and potentially better
solutions (cuckoos) to replace
not-so-good solutions in the
nests.
In the simplest form, each
nest has one egg.
The algorithm can be
extended to more complicated
cases in which each nest has
multiple eggs representing a
set of solutions
Figure: 4
Sambhram Basu | Cuckoo Search Algorithm
8
Characteristics of Cuckoo search (cont)
The CS is based on three
idealized rules:
Each cuckoo lays one egg at
a time, and dumps it in a
randomly chosen nest.
The best nests with high
quality of eggs (solutions) will
carry over to the next
generations.
The number of available host
nests is 鍖xed, and a host can
discover an alien egg with
probability p [0,1] .
In this case, the host bird can
either throw the egg away or
abandon the nest to build a
completely new nest in a new
Figure: 5
Sambhram Basu | Cuckoo Search Algorithm
9
Levy Flights
In nature, animals search for
food in a random or
quasi-random manner.
Generally, the foraging path of
an animal is effectively a
random walk because the
next move is based on both
the current location/state and
the transition probability to the
next location.
The chosen direction implicitly
depends on a probability,
which can be modeled
mathematically.
Figure: 6
Sambhram Basu | Cuckoo Search Algorithm
10
Levy Flights (Cont.)
A L辿vy 鍖ight is a random walk
in which the step-lengths are
distributed according to a
heavy-tailed probability
distribution.
After a large number of steps,
the distance from the origin of
the random walk tends to a
stable distribution.
Figure: 7
Sambhram Basu | Cuckoo Search Algorithm
11
Cuckoo search Algorithm
Sambhram Basu | Cuckoo Search Algorithm
12
Cuckoo search Algorithm (Cont)
The following steps describe the main concepts of Cuckoo
search algorithm
Step1. Generate initial population of n host nests.
Figure: 8
ai , ri : a candidate for optimal parameters
Sambhram Basu | Cuckoo Search Algorithm
13
Step2. Lay the egg ak, bk
the k nest.
K nest is randomly selected.
Cuckoos egg is very similar to
host egg.
where
ak = ak+RANDOMWALK(Levy鍖ight)ak
rk = rk+RANDOMWALK(Levy鍖ight)rk Figure: 9
Sambhram Basu | Cuckoo Search Algorithm
14
Step3. Compare the 鍖tness of
cuckoos egg with the 鍖tness
of the host egg.
Root Mean Square Error
(RMSE)
Figure: 10
Sambhram Basu | Cuckoo Search Algorithm
15
Step4. If the 鍖tness of
cuckoos egg is better than
host egg, replace the egg in
nest k by cuckoos egg.
Figure: 11
Sambhram Basu | Cuckoo Search Algorithm
16
Step5. If host bird notice it, the nest is abandoned and new one
is built. (p <0.25) (to avoid local optimization)
Figure: 12
Iterate steps 2 to 5 until termination criterion satis鍖ed
Sambhram Basu | Cuckoo Search Algorithm
17
Application of the CS Algorithm
Engineering optimization problems
NP hard combinatorial optimization problems
Data fusion in wireless sensor networks
Nanoelectronic technology based operation-ampli鍖er
(OP-AMP)
Train neural network
Manufacturing scheduling
Nurse scheduling problem
Sambhram Basu | Cuckoo Search Algorithm
18
References
Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier,
(2014).
Xin-She Yang, Cuckoo Search and Fire鍖y Algorithm: Theory and
Applications, Springer, (2013).
Xin-She Yang and Suash Deb, Multiobjective cuckoo search for
design optimization, Computers Operations Research, 40(6),
16161624 (2013).
Some contents are taken from the original slides in
The Use of Cuckoo Search in Estimating the Parameters of
Software Reliability Growth Models 2013. 8. 7 Taehyoun Kim
Sambhram Basu | Cuckoo Search Algorithm
19
Sambhram Basu | Cuckoo Search Algorithm

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  • 1. Department Of Computer Science Engineering Seemanta Engineering College Jharpokharia,Mayurbhanj,757086 Cuckoo Search Algorithm Under the supervision of Er. Abhimanyu sahu Sambhram Basu Roll No:2016P43 Regd No:1601201095 November 1, 2019
  • 2. 1 presentation Outline Introduction Cuckoo search algorithm (History and main idea) Behavior of Cuckoo breeding Behavior of Cuckoo breeding (Cont.) Characteristics of Cuckoo search Characteristics of Cuckoo search (cont) Levy Flights Levy Flights (Cont.) Cuckoo search Algorithm Cuckoo search Algorithm (Cont) Application of the CS Algorithm References Sambhram Basu | Cuckoo Search Algorithm
  • 3. 2 Introduction In operations research, cuckoo search is an optimization algorithm developed by Xin-she Yang and Suash Deb in 2009.[1][2] It was inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species). Some host birds can engage direct con鍖ict with the intruding cuckoos. For example, if a host bird discovers the eggs are not their own, it will either throw these alien eggs away or simply abandon its nest and build a new nest elsewhere. Some cuckoo species such as the New World brood-parasitic Tapera have evolved in such a way that female parasitic cuckoos are often very specialized in the mimicry in colors and pattern of the eggs of a few chosen host species.[3] Cuckoo search idealized such breeding behavior, and thus can be applied for various optimization problems. Sambhram Basu | Cuckoo Search Algorithm
  • 4. 3 Cuckoo search algorithm (History and main idea) A method of global optimization based on the behavior of cuckoos was proposed by Yang Deb (2009). The original cuckoo search (CS) algorithm is based on the idea of the following :- How cuckoos lay their eggs in the host nests. How, if not detected and destroyed, the egg are hatched to chicks by the hosts. How a search algorithm based on such a scheme can be used to 鍖nd the global Figure: Yang Deb Sambhram Basu | Cuckoo Search Algorithm
  • 5. 4 Behavior of Cuckoo breeding The CS was inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of host birds. Some cuckoos have evolved in such a way that female parasitic cuckoos can imitate the colors and patterns of the eggs of a few chosen host species. This reduces the probability of the eggs being abandoned and, therefore, increases their reproductivity . Figure: 1 Sambhram Basu | Cuckoo Search Algorithm
  • 6. 5 Behavior of Cuckoo breeding (Cont.) If host birds discover the eggs are not their own, they will either throw them away or simply abandon their nests and build new ones. Parasitic cuckoos often choose a nest where the host bird just laid its own eggs. In general, the cuckoo eggs hatch slightly earlier than their host eggs. Figure: 2 Sambhram Basu | Cuckoo Search Algorithm
  • 7. 6 Once the 鍖rst cuckoo chick is hatched, his 鍖rst instinct action is to evict the host eggs by blindly propelling the eggs out of the nest. This action results in increasing the cuckoo chicks share of food provided by its host bird . Moreover, studies show that a cuckoo chick can imitate the call of host chicks to gain access to more feeding opportunity. Figure: 3 Sambhram Basu | Cuckoo Search Algorithm
  • 8. 7 Characteristics of Cuckoo search Each egg in a nest represents a solution, and a cuckoo egg represents a new solution. The aim is to employ the new and potentially better solutions (cuckoos) to replace not-so-good solutions in the nests. In the simplest form, each nest has one egg. The algorithm can be extended to more complicated cases in which each nest has multiple eggs representing a set of solutions Figure: 4 Sambhram Basu | Cuckoo Search Algorithm
  • 9. 8 Characteristics of Cuckoo search (cont) The CS is based on three idealized rules: Each cuckoo lays one egg at a time, and dumps it in a randomly chosen nest. The best nests with high quality of eggs (solutions) will carry over to the next generations. The number of available host nests is 鍖xed, and a host can discover an alien egg with probability p [0,1] . In this case, the host bird can either throw the egg away or abandon the nest to build a completely new nest in a new Figure: 5 Sambhram Basu | Cuckoo Search Algorithm
  • 10. 9 Levy Flights In nature, animals search for food in a random or quasi-random manner. Generally, the foraging path of an animal is effectively a random walk because the next move is based on both the current location/state and the transition probability to the next location. The chosen direction implicitly depends on a probability, which can be modeled mathematically. Figure: 6 Sambhram Basu | Cuckoo Search Algorithm
  • 11. 10 Levy Flights (Cont.) A L辿vy 鍖ight is a random walk in which the step-lengths are distributed according to a heavy-tailed probability distribution. After a large number of steps, the distance from the origin of the random walk tends to a stable distribution. Figure: 7 Sambhram Basu | Cuckoo Search Algorithm
  • 12. 11 Cuckoo search Algorithm Sambhram Basu | Cuckoo Search Algorithm
  • 13. 12 Cuckoo search Algorithm (Cont) The following steps describe the main concepts of Cuckoo search algorithm Step1. Generate initial population of n host nests. Figure: 8 ai , ri : a candidate for optimal parameters Sambhram Basu | Cuckoo Search Algorithm
  • 14. 13 Step2. Lay the egg ak, bk the k nest. K nest is randomly selected. Cuckoos egg is very similar to host egg. where ak = ak+RANDOMWALK(Levy鍖ight)ak rk = rk+RANDOMWALK(Levy鍖ight)rk Figure: 9 Sambhram Basu | Cuckoo Search Algorithm
  • 15. 14 Step3. Compare the 鍖tness of cuckoos egg with the 鍖tness of the host egg. Root Mean Square Error (RMSE) Figure: 10 Sambhram Basu | Cuckoo Search Algorithm
  • 16. 15 Step4. If the 鍖tness of cuckoos egg is better than host egg, replace the egg in nest k by cuckoos egg. Figure: 11 Sambhram Basu | Cuckoo Search Algorithm
  • 17. 16 Step5. If host bird notice it, the nest is abandoned and new one is built. (p <0.25) (to avoid local optimization) Figure: 12 Iterate steps 2 to 5 until termination criterion satis鍖ed Sambhram Basu | Cuckoo Search Algorithm
  • 18. 17 Application of the CS Algorithm Engineering optimization problems NP hard combinatorial optimization problems Data fusion in wireless sensor networks Nanoelectronic technology based operation-ampli鍖er (OP-AMP) Train neural network Manufacturing scheduling Nurse scheduling problem Sambhram Basu | Cuckoo Search Algorithm
  • 19. 18 References Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, (2014). Xin-She Yang, Cuckoo Search and Fire鍖y Algorithm: Theory and Applications, Springer, (2013). Xin-She Yang and Suash Deb, Multiobjective cuckoo search for design optimization, Computers Operations Research, 40(6), 16161624 (2013). Some contents are taken from the original slides in The Use of Cuckoo Search in Estimating the Parameters of Software Reliability Growth Models 2013. 8. 7 Taehyoun Kim Sambhram Basu | Cuckoo Search Algorithm
  • 20. 19 Sambhram Basu | Cuckoo Search Algorithm