MATLAB的变色龙算法的优化代码

MATLAB的变色龙算法的优化代码如下：

function [bestSolution, bestFitness] = chamaleon(nPop, nVar, maxIt, lb, ub, fobj)

% Initialize the population
popPosition = repmat(lb, nPop, nVar) + rand(nPop, nVar) .* repmat((ub - lb), nPop, 1);
popFitness = zeros(nPop, 1);

% Compute the fitness of the initial population
for i = 1:nPop
    popFitness(i) = fobj(popPosition(i, :));
end

% Initialize the best solution and best fitness
[bestFitness, bestIndex] = min(popFitness);
bestSolution = popPosition(bestIndex, :);

% Main loop
for it = 1:maxIt
    % Compute the distance between each pair of individuals
    dist = pdist2(popPosition, popPosition);
    
    % Compute the fitness difference between each pair of individuals
    fitDiff = repmat(popFitness, 1, nPop) - repmat(popFitness', nPop, 1);
    
    % Compute the probability of each individual to change its position
    p = exp(-fitDiff ./ dist);
    p = p ./ repmat(sum(p, 2), 1, nPop);
    
    % Select a random individual to change its position
    i = randi(nPop);
    
    % Compute the new position of the selected individual
    newPosition = popPosition(i, :) + (ub - lb) .* (rand(1, nVar) - 0.5);
    newPosition = max(newPosition, lb);
    newPosition = min(newPosition, ub);
    
    % Compute the fitness of the new position
    newFitness = fobj(newPosition);
    
    % Update the population if the new individual is better
    if newFitness < popFitness(i)
        popPosition(i, :) = newPosition;
        popFitness(i) = newFitness;
        
        % Update the best solution and best fitness
        if popFitness(i) < bestFitness
            bestSolution = popPosition(i, :);
            bestFitness = popFitness(i);
        end
    else
        % Change the position of another individual according to the
        % probability distribution
        j = randsample(nPop, 1, true, p(i, :));
        popPosition(i, :) = popPosition(j, :);
        popFitness(i) = popFitness(j);
    end
end
end

注意：本代码中的 `fobj` 是适应度函数，需要用户自己定义。另外，本代码中的变色龙算法是基于距离和适应度差异的概率模型实现的。如果需要实现其他变色龙算法，请参考相关文献并进行相应的修改。