1

A seminar I On

Cuckoo Search Optimization Presented By-

Miss. Anuja Joshi

Guided By-Prof Dr. Kakandikar .G . M.

Dyanganga College Of Engineering and Research,Pune

2

Different Types of

Algorithms

Types Of Algorithms

3

What is Cuckoo Search?

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).

4 Cuckoo Behavior

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.

5 Cuckoo Behavior 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

6Consequence

Some host birds can engage direct conflict 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.

7

Three idealized rules of Cuckoo Search

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 no. of available host nests is fixed , and a host can discover an alien egg with probability (0,1).

8

Representations

9 Each egg in a nest represents a solution, and a

cuckoo egg represents a new solution.

The aim is to use the new and potentially better solutions (cuckoos) to replace a not-so-good solution 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.

10

Levi Flight

A Levi flight is a random walk in which the steps are defined in terms of the step-lengths, which have a certain probability distribution, with the directions of the steps being isotropic and random.

11

What is the algorithm?&How does it work?

Begin Objective function f(x), x = (x1, ...,xd)T ; Initial a population of n host nests xi (i = 1, 2, ..., n);while (t <Max Generation) or (stop criterion) Get a cuckoo (say i) randomly by Lévy flights; Evaluate its quality/fitness Fi; Choose a nest among n (say j) randomly;if (Fi >Fj) Replace j by the new solution;end Abandon a fraction (pa) of worse nests and build new ones at new locations via Lévy flights; Keep the best solutions (or nests with quality solutions); Rank the solutions and find the current best;end whilePost process results and visualization;End

12

13

Variants Of

Cuckoo Search

Variants Of Cuckoo Search

Binary Cuckoo Search

Improved Cuckoo Search

Modifi

ed

Cuckoo

Searc

h

14

Comparison with otherMeta Heuristic Algorithms

An important advantage of this

algorithm is its simplicity. Compared to other metaheuristic algorithms such as particle swarm optimization and harmony search, there is essentially only a single parameter in Cuckoo Search (apart from the population size n). Therefore, it is very easy to implement.

15

Advantages Of Cuckoo Search

Deals with multi-criteria

optimization problems

Easy to implement

Aims to speed up

convergence

Simplicity

It can be still

hybridized with other

swarm-based

algorithms

16

Applications

spring design and welded beam design problemsDesign optimization of truss structuresEngineering optimizationSteel framesWind turbine bladeReliability problemsStability analysis

The applications of Cuckoo Search in engineering optimization problems have shown its promising efficiency. Some of Applications are:-

17

REFERENCES

Ehsan Valian, Shahram Mohanna and Saeed Tavakoli,” Improved Cuckoo Search Algorithm for Feedforward Neural Network Training”, International Journal of Artificial Intelligence & Applications (IJAIA), Vol.2, No.3, July 2011,pp.36-46Iztok Fister Jr.a,Iztok Fistera,Xin-She Yangb,”A short discussion about Economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm”, International Journal of Applied Thermal Engineering 76 (2015) 535-537.Elham Shadkam and Mehdi Bijari,” Evaluation The Efficiency Of CuckooOptimization Algorithm”, International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.2, April 2014,pp.39-47.Basu M, Chowdhury A, “Cuckoo search algorithm for economic dispatch, Energy (2013)”, http://dx.doi.org/ 10.1016/j.energy.2013.07.011,pp.1-10

18

Pinar Civicioglu and Erkan Besdok,” A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms”, © Springer Science+Business Media B.V. 2011, 6 July 2011,pp.315-346Manjeet Kumar, Tarun Kumar Rawat,” Optimal design of FIR fractional order differentiator using cuckoo search 4 algorithm”,ScienceDirect,pp.-1-17Thang Trung Nguyen, Dieu Ngoc Vo,” Modified cuckoo search algorithm for short-term hydrothermal scheduling”,ScienceDirect,pp.-271-281Janusz Piechocki , Dominik Ambroziak , Aleksander Palkowski , Grzegorz Redlarski,” Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms”, ScienceDirect,pp.-901-908

19