改进禁忌搜索算法python

改进禁忌搜索算法有很多方法，这里介绍其中一种常见的改进方法——变邻域搜索策略。在原始的禁忌搜索算法中，邻域搜索策略通常是通过交换两个解中的元素来生成新的解。而变邻域搜索策略则是通过更复杂的操作来生成新的解，例如插入、删除或替换元素等。这样可以增加搜索空间，提高搜索效率。

下面是改进禁忌搜索算法的Python代码示例：

def improve_tabu_search(initial_solution, tabu_list, max_iterations):
    current_solution = initial_solution
    best_solution = current_solution
    tabu_list.append(current_solution)
    iteration = 0
    
    while iteration < max_iterations:
        neighbors = generate_neighbors(current_solution)
        best_neighbor = None
        
        for neighbor in neighbors:
            if neighbor not in tabu_list:
                if best_neighbor is None or evaluate(neighbor) < evaluate(best_neighbor):
                    best_neighbor = neighbor
        
        if best_neighbor is None:
            break
        
        current_solution = best_neighbor
        tabu_list.append(current_solution)
        
        if evaluate(current_solution) < evaluate(best_solution):
            best_solution = current_solution
        
        iteration += 1
    
    return best_solution

在上面的代码中，`initial_solution`是初始解，`tabu_list`是禁忌表，`max_iterations`是最大迭代次数。`generate_neighbors`函数用于生成当前解的邻居解，`evaluate`函数用于评估解的质量。