禁忌搜索算法matlab实现

禁忌搜索算法（Tabu Search）是一种启发式搜索算法，用于解决组合优化问题。它通过维护一个禁忌表来避免搜索过程中陷入局部最优解，并通过引入禁忌策略来探索更广泛的解空间。

以下是禁忌搜索算法的一种可能的MATLAB实现：

function [bestSolution, bestCost] = tabuSearch(initialSolution, costFunction, tabuListSize, maxIterations)
    currentSolution = initialSolution;
    bestSolution = currentSolution;
    bestCost = costFunction(currentSolution);
    tabuList = zeros(tabuListSize, numel(initialSolution));
    
    for iter = 1:maxIterations
        neighbors = generateNeighbors(currentSolution);
        bestNeighbor = [];
        bestNeighborCost = inf;
        
        for i = 1:numel(neighbors)
            neighbor = neighbors{i};
            neighborCost = costFunction(neighbor);
            
            if ~isTabu(neighbor, tabuList) && neighborCost < bestNeighborCost
                bestNeighbor = neighbor;
                bestNeighborCost = neighborCost;
            end
        end
        
        currentSolution = bestNeighbor;
        tabuList = updateTabuList(tabuList, currentSolution);
        
        if bestNeighborCost < bestCost
            bestSolution = bestNeighbor;
            bestCost = bestNeighborCost;
        end
    end
end

function neighbors = generateNeighbors(solution)
    % 生成当前解的邻居解
    % 实现略
end

function isTabu = isTabu(solution, tabuList)
    % 判断当前解是否在禁忌表中
    % 实现略
end

function updatedTabuList = updateTabuList(tabuList, solution)
    % 更新禁忌表
    % 实现略
end

在上述代码中，`initialSolution`是初始解，`costFunction`是评估解的成本函数，`tabuListSize`是禁忌表的大小，`maxIterations`是最大迭代次数。算法通过生成邻居解、判断解是否在禁忌表中以及更新禁忌表来实现禁忌搜索的过程。

请注意，上述代码只是禁忌搜索算法的一种简单实现，具体的实现方式可能因问题而异。你可以根据具体的问题需求进行相应的修改和优化。