# genetic algorithm example

Τεχνίτη Νοημοσύνη και Ρομποτική

23 Οκτ 2013 (πριν από 4 χρόνια και 5 μήνες)

119 εμφανίσεις

Genetic Algorithm

Example based on

Koza, J. 1993.
Genetic Programming.

Cambridge MA: Basic Books

D Goforth
-

COSC 4117, fall 2006

2

Avoiding paths altogether

genetic algorithms

1.
pick set of states randomly

2.
order states by fitness

3.
create new set of states by combining
state variables of most fit

4.
make a few random changes to state
variables

5.
go to 2

D Goforth
-

COSC 4117, fall 2006

3

Example: Koza, based on
Goldberg and Samtani in 1986

Problem minimize cost of 10
-
member truss that
meets stress requirements

100kg

100kg

8m

8m

6m

A10

A1

A2

A3

A4

A5

A6

A7

A8

A9

D Goforth
-

COSC 4117, fall 2006

4

Example: Koza, based on
Goldberg and Samtani in 1986

Problem minimize cost of 10
-
member truss that
meets stress requirements

100kg

100kg

8m

8m

6m

A10

A1

A2

A3

A4

A5

A6

A7

A8

A9

D Goforth
-

COSC 4117, fall 2006

5

Problem definition

16 levels of strength for
beams based on cross
-
section; cost increases
with cross
-
section

Stress requirements for
the truss

Goal: minimize cost of
safe truss

100kg

100kg

8m

8m

6m

A10

A1

A2

A3

A4

A5

A6

A7

A8

A9

Cost is minimized by minimizing truss weight = cross
-
section * length

Stress calculations are based on all member weights (succeed/fail)

D Goforth
-

COSC 4117, fall 2006

6

Problem representation

Represent cross
-
sections by 4
-
bit binary code

Represent a particular design by 10x4=40 bits

E.g.,
0110 1101 0101 0101 1011 0110 1010 1010 1111 0111

A1 A2 A3 A4 A5 A6 A7 A8 A9 A10

State space is set of all possible designs

2
40

designs

No obvious start state; no “path” to solution

Genetic algorithm

D Goforth
-

COSC 4117, fall 2006

7

Genetic Algorithm I

1.
pick set of states randomly (initial population)

0110 1101 0101 0101 1011 0110 1010 1010 1111 0111 (351)

1011 0110 1010 1010 1111 1101 0101 0111 0110 0101 (377)

1101 1011 0110 1010 0110 1111 1101 0101 1010 0111 (391)

0110 1101 1011 0101 0101 0110 1111 0111 1010 1010 (438)

1001 0111 0101 1011 0110 1010 1010 0110 1101 0101 (fail)

1111 0111 0110 1101 0101 0101 1011 0110 1010 1010 (fail)

2.
order states by fitness (
weight, stress
)

D Goforth
-

COSC 4117, fall 2006

8

Genetic Algorithm II

3.
create new set of states by combining state
variables of (3) most fit and replacing least fit

1011 0110 1010 1010
1011 0110 1010 1010 1111 0111
(337)

0110 1101 0101 0101 1011 0110 1010 1010 1111 0111 (351)

0110 1101 0101 0101 1011 0110
1101 0101 1010 0111
(366)

0110 1101 010
0

0101
1111 1101 0101 0111 0110 0101
(370)

1011 0110 1010 1010 1111 1101
1
101 0111 0110 0101 (377)

1101 1011 0110 1010 0110 1111 1101 0101 1010 0111 (391)

4.
make a few mutations (random changes to
variables)

5.
go to 2

repeat until no more improvement in best fitness