Let’s see the power of my adaptive restart genetic algorithm

Hello everyone and welcome!

In this post, I’m going to show you my adaptive restart genetic algorithm for solving optimization problems.

This innovative genetic algorithm with adaptive restart mechanism is proposed to improve the success rate of achieving global optimal solution of the algorithm.

Here is the general structure of my adaptive restart genetic algorithm.

Here are the details of the benchmark function.

Let’s see how my adaptive restart genetic algorithm works.

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population.m

function Y = population(n)
% n = population size
% 60 = number of bits to express the number. Why? It depends on
% the required accuracy (the number of digits after comma) that we want
Y=round(rand(n,60));

crossover.m

function Y=crossover(P,n)
% P = population
% n = pair of chromosomes to be crossovered
[x1 y1]=size(P);
Z=zeros(2*n,60);
for i = 1:n
    r1=randi(x1,1,2);
    while r1(1)==r1(2)
        r1=randi(x1,1,2);
    end
    A1=P(r1(1),:);
    A2=P(r1(2),:);
    r2=1+randi(59);
    B1=A1(1,r2:60);
    A1(1,r2:60)=A2(1,r2:60);
    A2(1,r2:60)=B1;
    Z(2*i-1,:)=A1;
    Z(2*i,:)=A2;
end
Y=Z;

mutation.m

function Y=mutation(P,n)
% P = population
% n = chromosomes to be mutated
[x1 y1]=size(P);
Z=zeros(n,60);
for i = 1:n
    r1=randi(x1);
    A1=P(r1,:);
    r2=randi(60,1,2);
    while r2(1)==r2(2)
        r2=randi(60,1,2);
    end
    B1=A1(1,r2(1));
    A1(1,r2(1))=A1(1,r2(2));
    A1(1,r2(2))=B1;
    Z(i,:)=A1;
end
Y=Z;

evaluation.m

function Y=evaluation(P)
[x1 y1]=size(P);
H=zeros(x1,1);
for i = 1:x1
    A=bi2de(P(i,1:30));
    x=-100+A*(100-(-100))/(2^30-1);
    B=bi2de(P(i,31:60));
    y=-100+B*(100-(-100))/(2^30-1);
    H(i,1)= ((sin(x-y/8))^2 + (sin(y+x/8))^2)/(sqrt((x-8.6998)^2 + (y-6.7665)^2) +1);
end
Y=H;

selection.m

…

Sorry! This is only a half of the code.

Notice: It would take you from 1 to 3 hours to re-type the Matlab code yourself; or with just €3.99 (the cost of a cup of coffee), you can download/copy the whole Matlab code within 2 minutes. It’s your choice to make.

Original price is €9.99 but today it’s only €3.99 (save €6 today – available for a limited time only)

Download the whole Matlab code here (Membership Code ID: 018)

No need to build the Matlab code from scratch because it’s very time-consuming. My idol, Jim Rohn, once said: “Time is more value than money. You can get more money, but you cannot get more time”. If you think this code can be used in your research/teaching work, you should download it and then customize/modify/apply it to your work, without any obligation of citing the original source if you don’t want. However, redistribution (i.e., downloading the code/script here and then making it available on another site on the Internet) is strictly prohibited.

If you have any question or problem, please contact Dr. Panda by email: learnwithpanda2018@gmail.com

Thank you very much and good luck with your research!