README.md

Gravitational Search Algorithm

Reference: Rashedi E, Nezamabadi-Pour H, Saryazdi S. GSA: a gravitational search algorithm[J]. Information Sciences, 2009, 179(13): 2232-2248.

Variables	Meaning
pop	Population size
iter	Iteration number
lb	The lower bound (list)
ub	The upper bound (list)
pos	The position of agents (list)
score	The score of agents (list)
mass	The mass of agents (list)
acc	The acceleration of agents (list)
vel	The velocity of agents (list)
G	The gravitational constant
dim	Dimension
gbest	The score of the global best agent
iter_best	The global best score of each iteration (list)
con_iter	The last iteration number when "gbest" is updated

Test problem

$$ f(x)=\sum_{i=1}^{30}x_i^2,\qquad -100\leq x_i\leq100, \quad i=1,\cdots, 30. $$

Example

clear all;
clc;

pop = 50;
iter = 1000;
lb = ones(1, 30) .* (-100);
ub = ones(1, 30) .* 100;
[gbest, gbest_pos, iter_best, con_iter] = GSA(pop, iter, lb, ub);

% Plot the convergence curve
x = 1 : iter;
loglog(x, iter_best);
grid on;
title('Convergence curve');
xlabel('Iteration');
ylabel('Objective value');

Output:

The GSA converges at its 999-th iteration, and the global best value is 2.1691e-17.