The Delivery Man Problem with Time Windows (DMPTW) is an extension of the Delivery Man Problem. The objective of DMPTW is to minimize the sum of customers’ arrival time while the deliveries are made during a specific time window given by the customers. Another close variant of objective is a travel duration. In the case, the problem minimizes the sum of travel durations between a depot and customer locations. It has many practical applications to network problems, e.g., whenever servers have to accommodate a set of requests to minimize clients’ total (or average) waiting time. To solve medium to large-sized instances, a two-phase metaheuristic algorithm is proposed. A construction stage generates a feasible solution using Neighborhood Descent with Random neighborhood ordering (RVND), and the optimization stage improves the feasible solution with an Iterated Local Search. Moreover, Tabu Search (TS) is incorporated in the proposed algorithm to prevent it from getting trapped into cycles. Therefore, our algorithm is prevented from becoming stuck at local optima. The results of experimental simulations are compared with well-known and successful metaheuristic algorithms. These results show that the proposed algorithm reaches better solutions in many cases.

带时间窗口的送货人问题（DMPTW）是送货人问题的扩展。DMPTW的目的是在客户给定的特定时间范围内交货时，最大程度地减少客户到达时间的总和。物镜的另一个近似变体是旅行持续时间。在这种情况下，该问题使仓库与客户地点之间的行驶时间之和最小化。它在解决网络问题方面有许多实际应用，例如，每当服务器必须容纳一组请求以最小化客户端的总（或平均）等待时间时。针对大中型实例，提出了一种两阶段元启发式算法。施工阶段使用具有随机邻域顺序（RVND）的邻域下降生成可行的解决方案，优化阶段通过迭代局部搜索改进了可行的解决方案。此外，禁忌搜索（TS）被并入提出的算法中，以防止其陷入循环。因此，可以防止我们的算法陷入局部最优状态。实验模拟的结果与众所周知的成功的元启发式算法进行了比较。这些结果表明，该算法在许多情况下都能达到较好的解决方案。