PowerPoint Presentation

: : : :

95

Evolutionary Algorithms (EA) GA GA GA Genetic Programming crossover GP

Genetic Algorithm# / 32

1970 . . . .

Genetic Algorithm# / 32

(Heuristic)(Non-deterministic)(Estimation of Distribution Algorithms)(Evolutionary Algorithms)(Population-based)(Search Strategies)

Genetic Algorithm# / 32

Genetic Algorithm# / 32

.

Genetic Algorithm# / 32

(Artificial life) ) (Classification ((DM ((ML .

Genetic Algorithm# / 32

Genetic Algorithm# / 32

Evolutionary Algorithms (EA)

. .

Genetic Algorithms : bit String .

Genetic Programming : lisp .

Genetic Algorithm# / 32

population (Fitness) . . GA

Genetic Algorithm# / 32

GAGA(Fitness,Fitness_threshold,p,r,m)

Fitness : .( )Fitness_threshold: .P : .r: crossover .m: mutation

Genetic Algorithm# / 32

. : : 100 . . .

.

Genetic Algorithm# / 32

:

1 2 3 ( Fitness ) 4 ( ) 5 .

Genetic Algorithm# / 32

CrossOver :

.

:single -point crossoverTwo -point crossover Uniform crossover

Crossovermutation

crossover mask .

.

Genetic Algorithm# / 32

Single-Point CrossOver

Crossover mask : 1110000

Genetic Algorithm# / 32

Tow-Point CrossOver

Crossover mask

Genetic Algorithm# / 32

Uniform CrossOver Uniform Crossover .

: Pc crossover : : Pc .

Crossover mask

Genetic Algorithm# / 32

Mutation

. :

. :

: .

Pm . . Pg .

Mutatuin :

(Bitwise Mutation )

(Heuristic) . . .

Genetic Algorithm# / 32

0000000000000

0011000100100

:

( Bitwise Mutation)

Genetic Algorithm# / 32

Mutation Crossover explorative Exploitive . .MutationCrossover

Genetic Algorithm# / 32

fitness . :: classification .

Genetic Algorithm# / 32

22 Roulette Wheel selection GA fitness fitness . Roulette Wheel selection .

P(hi) = Fitness (hi) / j Fitness (hj)fitness(A) = 3fitness(B) = 1fitness(C) = 2

AC1/6 = 17%3/6 = 50%B2/6 = 33%

:tournament selectionrank selection : . .

Genetic Algorithm# / 32

GA . Gradient descent GA . GA . GA crowding

.

Ranking GA

Genetic Algorithm# / 32

. GP . pars .Genetic Programming+sinxsqrt+y^x2F = sin(x) + sqrt( x^2 + y)

Genetic Algorithm# / 32

crossover GPparents+sinx^2+sinxsqrt+ychildrens+sinx^2

+yx

^x2

^x2+sinxsqrt+y

+yx

Genetic Algorithm# / 32

Genetic Algorithm# / 32

Genetic Algorithm# / 32

1 - .

2

1- ( Generation Iteration) 2- 3-

Genetic Algorithm# / 32

( ) .

. . .

Genetic Algorithm# / 32

1.https://fa.wikipedia.org/wiki/%D8%A7%D9%84%DA%AF%D9%88%D8% B1%DB%8C%D8%AA%D9%85_%DA%98%D9%86%D8%AA%DB%8C %DA%A9

2.http://www.google.com/url?sa=t&rct=j&q=&esrc=s&frm=1&source=web& cd=4&ved=0ahUKEwjTkvKF3fLJAhVB44MKHccpAYkQFgg6MAM&url =http%3A%2F%2Fceit.aut.ac.ir%2F~shiry%2Flecture%2FDSS%2FGA.ppt &usg=AFQjCNGJEmoV68oTejxF9KCAFernYdWaJQ&bvm=bv.11015184 a4,d.eWE&cad=rj

3. algorithms.html-http://www.beytoote.com/scientific/midanid/genetic

Genetic Algorithm# / 32

Genetic Algorithm# / 32

Genetic Algorithm# / 32