% -------------------------------------------------
% Citation details:
% Alireza Askarzadeh, Anovel metaheuristic method for solving constrained
% engineering optimization problems: Crow search algorithm, Computers &
% -------------------------------------------------
format long; close all; clear all; clc
pd=10; % Problem dimension (number of decision variables)
N=20; % Flock (population) size
AP=0.1; % Awareness probability
fl=2; % Flight length (fl)
[x l u]=init(N,pd); % Function for initialization
xn=x;
ft=fitness(xn,N,pd); % Function for fitness evaluation
mem=x; % Memory initialization
fit_mem=ft; % Fitness of memory positions
tmax=5000; % Maximum number of iterations (itermax)
for t=1:tmax
num=ceil(N*rand(1,N)); % Generation of random candidate crows for following (chasing)
for i=1:N
if rand>AP
xnew(i,:)= x(i,:)+fl*rand*(mem(num(i),:)-x(i,:)); % Generation of a new position for crow i (state 1)
else
for j=1:pd
xnew(i,j)=l-(l-u)*rand; % Generation of a new position for crow i (state 2)
end
end
end
xn=xnew;
ft=fitness(xn,N,pd); % Function for fitness evaluation of new solutions
for i=1:N % Update position and memory
if xnew(i,:)>=l & xnew(i,:)<=u
x(i,:)=xnew(i,:); % Update position
if ft(i)<fit_mem(i)
mem(i,:)=xnew(i,:); % Update memory
fit_mem(i)=ft(i);
end
end
end
ffit(t)=min(fit_mem); % Best found value until iteration t
min(fit_mem)
end
ngbest=find(fit_mem== min(fit_mem));
g_best=mem(ngbest(1),:); % Solutin of the problem
