Presentation On Genetic Algorithms

PPT On Genetic Algorithms

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Genetic Algorithms Presentation Transcript:
1.Genetic Algorithms

2.Introduction to Genetic Algorithms
A class of probabilistic optimization algorithms
Inspired by the biological evolution process
Uses concepts of “Natural Selection” and “Genetic Inheritance” (Darwin 1859)
Originally developed by John Holland (1975)
Particularly well suited for hard problems where little is known about the underlying search space
Widely-used in business, science and engineering

3.Applications of GA
Parameter and System Identification
Control
Robotics
Pattern Recognition
Speech Recognition
Engineering Designs
Planning and Scheduling
Classifier System

4.Simple Genetic Algorithm
produce an initial population of individuals
evaluate the fitness of all individuals
while termination condition not met do
    select fitter individuals for reproduction
    recombine between individuals
    mutate individuals
    evaluate the fitness of the modified individuals
    generate a new population
End while

5.It is an iterative optimization procedure.
GA works with no. of solutions in each iteration, known as population.

6.GA: Flowchart for working principle

7.Representation
All x(i)’s are string structure coded.
Strings could be real, binary, alphabetical etc.

8.Representation

9.Reproduction
It selects good set of strings and found the mating pool.
Probability of selection of string in mating pool is directly proportional to fitness of string

10.Crossover & Mutation
After applying reproduction with all included steps, crossover & mutation are applied on the string.
And then the average fitness of finally mutated string is compared with string in last iteration.
If F2 > F1, then the solution is considered to improved.
Likewise problem is solved for user defined no. of iterations.