MATLAB的变色龙优化算法代码
时间: 2023-09-30 09:06:30 浏览: 47
以下是MATLAB实现的变色龙优化算法代码:
```matlab
function [best_fit, best_sol] = chameleon_optimization(func, dim, lb, ub, max_iter, pop_size, c, p)
% 变色龙优化算法
% func:目标函数
% dim:解向量维度
% lb:各变量下界
% ub:各变量上界
% max_iter:最大迭代次数
% pop_size:种群大小
% c:追踪因子,取值范围(0,1)
% p:突变概率,取值范围(0,1)
% best_fit:最优解的适应值
% best_sol:最优解
% 初始化
pop = repmat(lb, pop_size, 1) + rand(pop_size, dim) .* repmat((ub - lb), pop_size, 1);
fitness = feval(func, pop');
[best_fit, best_idx] = min(fitness);
best_sol = pop(best_idx, :);
iter = 1;
while iter <= max_iter
% 突变
for i = 1 : pop_size
if rand() < p
x = pop(i, :);
x_new = x + randn(1, dim) .* abs(best_sol - x) * c;
x_new = max(x_new, lb);
x_new = min(x_new, ub);
f_new = feval(func, x_new');
if f_new < fitness(i)
fitness(i) = f_new;
pop(i, :) = x_new;
end
end
end
% 追踪
for i = 1 : pop_size
for j = 1 : dim
if rand() < c
x = pop(i, :);
x(j) = x(j) + randn() * abs(best_sol(j) - x(j));
x = max(x, lb);
x = min(x, ub);
f_new = feval(func, x');
if f_new < fitness(i)
fitness(i) = f_new;
pop(i, :) = x;
end
end
end
end
% 更新最优解
[f_min, idx_min] = min(fitness);
if f_min < best_fit
best_fit = f_min;
best_sol = pop(idx_min, :);
end
% 输出信息
fprintf('Iteration %d: Best Cost = %f\n', iter, best_fit);
iter = iter + 1;
end
end
```
其中,`func`为目标函数,`dim`为解向量的维度,`lb`和`ub`分别为各变量的下界和上界,`max_iter`为最大迭代次数,`pop_size`为种群大小,`c`为追踪因子,`p`为突变概率。函数返回最优解的适应值和最优解。