CUCKOO SEARCH

By : Biswajit Panday

1Ahsanullah University of Science & Technology

Email : biswajitmailid@gmail.com

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Cuckoo search (CS) is an optimization algorithm developed by Xin-she Yang and Suash Deb in 2009.

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).

Overview

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Cuckoos have an aggressive reproduction strategy that involves the female laying her fertilized eggs in the nest of another species so that the surrogate parents unwittingly raise her brood. Sometimes the cuckoo's egg in the host nest is discovered (eggs are not its owns), the surrogate parents either throw it out or abandon the nest and builds their own brood elsewhere.

Some cuckoo species have evolved in such a way that female parasitic cuckoos are often very specialized in the mimicry in color and pattern of the eggs of a few chosen host species. This reduces the probability of eggs being abandoned and increases their reproductively.

Cuckoo Behavior

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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.

Recently laid egg by other

species.

Cuckoo Behavior

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Once the first cuckoo chick is hatched, the first instinct action it will take is to evict the host eggs by blindly propelling the eggs out of the nest, which increases the cuckoo chick’s share of food provided by its host bird.

Cuckoo Behavior

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1) Each cuckoo lays one egg at a time, and dumps it in a randomly

chosen nest.

2) The best nests with high quality of eggs (solutions) will carry

over to the next generations.

3) The number of available host nests is fixed, and a host can

discover an alien egg with a probability pa ∈ [0, 1]. In this

case, the host bird can either throw the egg away or abandon the

nest so as to build a completely new nest in a new location.

Cuckoo Rules & parameters

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Begin Objective function f(x), x = (x1, ..., xd)T ; Initial a population of n host nests xi (i = 1, 2, ..., n); while (t <MaxGeneration) or (stop criterion)

Get a cuckoo (say i) randomly by Lévyflights; Evaluate its quality/fitness Fi; Choose a nest among n (say j) randomly; if (Fi > Fj) Replace j by the new solution; end

A fraction (pa) of worse nests are abandon and new once are built. Keep the best solutions (or nests with quality solutions);

Rank the solutions and find the current best; end while Post-process results and visualization; End

Pseudo Code of Cuckoo Search Algorithm

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Start

End

Initialize population size

Initialize the initial fitness

Iteration<max &max

fitness>accuracy

Calculate center of chromosome

Calculate number of eggs

Calculate radius

Calculate radiuses

Determine position of best chromosome to be copied to next generation

Apply crossover

Make clusters and determine the best clusters

Update the chromosome and copy the best one to the new generation

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a) Spring design and Welded beam design problems.

b) Solve nurse scheduling problem.

c) An efficient computation for data fusion in wireless sensor

networks.

d) A new quantum-inspired cuckoo search was developed to

solve Knapsack problems.

e) Efficiently generate independent test paths for structural

software testing and test data generation.

f) Applied to train neural networks with improved

performance.

Cuckoo Applications

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Thank You…For your attention