Week 5 - Genetic Algorithm
Genetic Algorithm
By Aby Abraham Chandy
Aim: -
Find the Global Maxima of the Stalagmite Function and plot 3 studies for Fmax vs No. of iteration
Explain GA function
GA Function: -
GA function uses the Genetic Algorithm to optimize the minimum value to identify the most stable state, or the most likely outcome.
To identify the max value of the Stalagmite Function we use the negative plots of the Stalagmite function as the GA function optimizes to the minimum Values.
x = ga(fun,nvars,A,b,Aeq,beq,lb,ub,nonlcon,intcon,options) –
GA function to optimize the function ‘fun’,
‘fun’ – function to find local minima
‘nvar’ - number of variables in the function.
‘lb’ – Lower bound
‘ub’ – upper bound
‘options’ - provide various solver options – ‘Population size’
Code Studies :-
3 Studies were conducted .
- general GA function without the options
- GA function with upper and Lower bounds
- GA function with bounds and defined Population size.
Each run of the program took different time.
More the parameter added to the GA command the more time it took, and the solution was more accurate.
|
Runs |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
|
S1_Timer = |
7.0242 |
7.02 |
7.5778 |
6.6393 |
7.3621 |
6.9105 |
7.0888 |
|
max_val1 = |
0.7611 |
0.7125 |
0.7722 |
0.7933 |
0.7322 |
0.7218 |
0.7012 |
|
S2_Timer = |
8.7122 |
8.1778 |
9.0387 |
7.7139 |
7.6861 |
7.995 |
7.839 |
|
max_val2 = |
0.9831 |
0.9607 |
0.9775 |
0.946 |
0.9607 |
0.9663 |
0.9663 |
|
S3_Timer = |
19.1971 |
18.3926 |
19.4116 |
18.6825 |
18.1238 |
18.0342 |
18.2976 |
|
max_val3 = |
1 |
1 |
1 |
0.9944 |
0.9944 |
0.9944 |
1 |