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CUCKOO SEARCH ALGORITHM
Transcript of CUCKOO SEARCH ALGORITHM
HISTORY OF METAHEURISTIC
Metaheuristics are strategies that "guide" the search process.
The goal is to efficiently explore the search in order to find near optimal solutions.
They may incorporate mechanisms to avoid getting trapped in confined areas of the search space.
The basic concepts of metaheuristics permit an abstract level description.
Metaheuristic is a problem-independent technique.
Application of metaheuristics falls into a large number of areas.Some them are;
-Planning in routing problems,Scheduling problems,Transportation,Robot planning etc.
-Ant colony optimization -Genetic Algorithm -Tabu search
-Bee colony -Simulated Annealing -Cuckoo search algorithm etc.
CUCKOO SEARCH ALGORITHM
CHARACTERISTIC OF CUCKOO SEARCH
APPLICATIONS OF CUCKOO ALGORITHM
The applications of Cuckoo Search in engineering optimization problems have solution its promising efficien.An interesting application of cuckoo search is to solve boundary value problems.More recently,cuckoo search algorithm is used for optimal parameter estimation of nonlinear Mskingum flood routing model.
The applications of Cuckoo in the various domains are briefed below.
Solve Nurse scheduling problems
Spring deign and Welded Beam design problems
Nano electronic technology based operation amplifier.
An efficient computation for data fusion in wireless
Reliability problems etc.
CUCKOO SEARCH ALGORITHM
AYŞE GÜLCE GÜNGÖR 20120603023
GAMZE KAR 20120603030
YAĞMUR ERDEM 20120603016
BEYZA DAVASLIGİL 20120603011
AYBERK ÇETİNKAYA 20120603009
ADVANTAGES OF CSA
FLOW CHART OF CSA
IMPORTANT STAGES INVOLVED IN CSA
CUCKOO SEARCH ALGORITHM FOR THE SELECTION OF OPTIMAL MACHINING PARAMETERS IN MILLING OPERATIONS
History of Metaheuristic
Cuckoo Search Algorithm
Characteristic of CSA
Applications of CSA
Advantages of CSA
The heuristic conception solving optimization problems -by Polya in 1945
The simplex algorithm -George Dantzig in 1947
To present the greedyheuristic in the combinatorial optimization literature -Jack Edmonds in 1971
1.1952-Robbins and Monro work on stochastic optimization methods.
2.1954-Barricelli carry out the first simulations of the evolution process and use them on general opimization problem
3.1963-Rastrigin proposes random search,etc..
Meta means in an "upper level",heuristic means "to find"
In computer science and mathematical optimization,a metaheuristic is a higher-level procedure.
Compared to optimization algorithm and iterative methods,metaheuristic do not guarantee that to find globally optimal solutions.
The optimum nest with great quality eggs is carried out the next generations.
The number of host nests are static and a host can find an alien egg with a probability, whose presence leads to either throwing away of the egg or abandoning the nest by the host bird.
Each egg in a nest represents a solution and cuckoo eggs represents the new solutions against weaker fitness solution.
i) initialization : Introduce a random population of n host nests i (Xi=1,2,3...n)
ii) Levy Flight Behavior :Obtain a cuckoo by levy flight behavior equation which is defines as follows:
Xi(t+1) = Xi(t) + alpha Levy (lambda), alpha>0
Levy(lambda)= t (- lambda), 1<lambda<3
iii) Fitness Function of the cuckoo egg (new solution) is compared the fitness of the host eggs (solutions).
Fitness Function = current best solution - previous best solution
Cuckoo Search is an optimization algorithm proposed by Yang&Deg in 2009.It was inspired by the obligation brood parasitism of some cuckoo species by laying their eggs in the nests of host birds.
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.
Each egg in a rest represent a solution,cuckoo eggs represents a new solution. The aim is to use the new and potentially better solutions 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.
CS is based on three rules:
1-Each cuckoo lays one eggs at time, and dumps its eggs in
a randomly choosen nest,
2-The best nests with high quality of eggs will carry over
to the next generation,
3-The number of available hosts nests is fixed and the egg
laid by a cuckoo is discovered by the host bird with
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 the both the current location and the transition probability to the next location. The chosen direction implicitly depends on a probability which can modeled mathematically.
The main goal in machining operations is to produce products with low-cost and high quality.In order to manufacture the highest quality product,current optimization technique must be improved.
CSA is used to optimize cutting parameters in milling operations.
For solving this case study we mainly use pseudo-code that we mentioned in previous slides.
Other possible future works include application of the CS to the metal cutting problems such as turnning,drilling,grinding,etc.operations manufacturing industry as well as design optimization problems.
The main advantage of Cuckoo Search is a good ability for finding the solution.
-Cuckoo Search is easy to implement and capable of finding feasible near global optimal solution
-Deals with multi-criteria optimization problems
-It can be still hybridized with order swarm-based algorithms
-Cuckoo Search is competitive
technique for solving complex
non smooth optimization problems
in power system operation
Cuckoo is flying randomly with levy algorithm.If seat is optimal cuckoo settle their eggs to seat.If cuckoo sets their egg to seat array will set by 1.With this Way we can calculate the probability of survive.We find the code via internet but we try to improve.
Also,old codes did not run and did not receive the result but in this java codes we success to run the codes.
Cuckoo search is one of the recent optimization algorithms in the league of nature based algorithm whose results are better than the PSO and ACO algorithms.
The applications of Cuckoo includes optimizing weights of neural networks,parameters of Support vector machines and Radial basis function,Job scheduling,finding optimal cluster head in wireless sensor networks,finding shortest path and clustering and is aimed to understand the breeding behavior of cuckoo bird.