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CUCKOO SEARCH ALGORITHM
Submited By-
Prachi Gulihar 31603216
Riya Bilaiya 31603223
Table of contents
1.Cuckoo search algorithm (History and main idea)
3. Characteristics of Cuckoo search
7. References
2. Behavior of Cuckoo breeding
6. Application of the Cuckoo search Algorithm
4. Lѐvy Flights
5. 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 eggs
are hatched to chicks by the hosts.
How a search algorithm based on such a
scheme can be used to find the global optimum
of a function.
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 .
•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.
•Once the first cuckoo chick is hatched,
his first instinct action is to evict the host
eggs by blindly propelling the eggs out
of the nest.
•This action results in increasing the
cuckoo chick’s 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.
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
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
fixed, and a host can discover an alien egg
with probability p ϵ [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
Lѐvy 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.
•A Lévy flight 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.
Cuckoo search Algorithm
The following steps describe the main concepts of Cuckoo
search algorithm
Step1. Generate initial population of n host nests.
( 𝑎𝑖,𝑟𝑖) : a candidate for optimal parameters
Steps of Cuckoo search
Step2. Lay the egg (𝑎𝑘′,𝑏𝑘′) in the k nest.
• K nest is randomly selected.
• Cuckoo’s egg is very similar to host egg.
Where
𝑎𝑘′=𝑎𝑘+𝑅𝑎𝑛𝑑𝑜𝑚𝑤𝑎𝑙𝑘(Lѐvy flight)𝑎𝑘
𝑟𝑘′=𝑟𝑘+𝑅𝑎𝑛𝑑𝑜𝑚𝑤𝑎𝑙𝑘(Lѐvy flight)𝑟𝑘
Step3. Compare the fitness of cuckoo’s egg with the fitness of
the host egg.
Root Mean Square Error (RMSE)
Step4. If the fitness of cuckoo’s egg is better than host egg,
replace the egg in nest k by cuckoo’s egg.
Step5. If host bird notice it, the nest is abandoned and new
one is built. (p <0.25) (to avoid local optimization)
Iterate steps 2 to 5 until termination criterion satisfied
Application of the CS Algorithm
•Engineering optimization problems
•NP hard combinatorial optimization problems
•Data fusion in wireless sensor networks
•Nanoelectronic technology based operation-amplifier
•Train neural network
•Manufacturing scheduling
•Nurse scheduling problem
References
Xin-She Yang, Nature-Inspired Optimization Algorithms,
Elsevier, (2014).
Xin-She Yang, Cuckoo Search and Firefly Algorithm: Theory
and Applications, Springer, (2013).
Thank you

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Cuckoo search

  • 1. CUCKOO SEARCH ALGORITHM Submited By- Prachi Gulihar 31603216 Riya Bilaiya 31603223
  • 2. Table of contents 1.Cuckoo search algorithm (History and main idea) 3. Characteristics of Cuckoo search 7. References 2. Behavior of Cuckoo breeding 6. Application of the Cuckoo search Algorithm 4. Lѐvy Flights 5. Cuckoo search Algorithm
  • 3. 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 eggs are hatched to chicks by the hosts. How a search algorithm based on such a scheme can be used to find the global optimum of a function.
  • 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 .
  • 5. •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.
  • 6. •Once the first cuckoo chick is hatched, his first instinct action is to evict the host eggs by blindly propelling the eggs out of the nest. •This action results in increasing the cuckoo chick’s 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.
  • 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
  • 8. 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 fixed, and a host can discover an alien egg with probability p ϵ [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
  • 9. Lѐvy 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.
  • 10. •A Lévy flight 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.
  • 12. The following steps describe the main concepts of Cuckoo search algorithm Step1. Generate initial population of n host nests. ( 𝑎𝑖,𝑟𝑖) : a candidate for optimal parameters Steps of Cuckoo search
  • 13. Step2. Lay the egg (𝑎𝑘′,𝑏𝑘′) in the k nest. • K nest is randomly selected. • Cuckoo’s egg is very similar to host egg. Where 𝑎𝑘′=𝑎𝑘+𝑅𝑎𝑛𝑑𝑜𝑚𝑤𝑎𝑙𝑘(Lѐvy flight)𝑎𝑘 𝑟𝑘′=𝑟𝑘+𝑅𝑎𝑛𝑑𝑜𝑚𝑤𝑎𝑙𝑘(Lѐvy flight)𝑟𝑘
  • 14. Step3. Compare the fitness of cuckoo’s egg with the fitness of the host egg. Root Mean Square Error (RMSE)
  • 15. Step4. If the fitness of cuckoo’s egg is better than host egg, replace the egg in nest k by cuckoo’s egg.
  • 16. Step5. If host bird notice it, the nest is abandoned and new one is built. (p <0.25) (to avoid local optimization) Iterate steps 2 to 5 until termination criterion satisfied
  • 17. Application of the CS Algorithm •Engineering optimization problems •NP hard combinatorial optimization problems •Data fusion in wireless sensor networks •Nanoelectronic technology based operation-amplifier •Train neural network •Manufacturing scheduling •Nurse scheduling problem
  • 18. References Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, (2014). Xin-She Yang, Cuckoo Search and Firefly Algorithm: Theory and Applications, Springer, (2013).