In this paper, we address a multi-compartment automatic guided vehicle scheduling (MC-AGVS) problem from a matrix manufacturing workshop that has attracted more and more attention of manufacturing firms in recent years. The problem aims to determine a solution to minimize the total cost including the travel cost, the service cost, and the cost of vehicles involved. For this purpose, a mixed-integer linear programming model is first constructed. Then, a novel iterated greedy (IG) algorithm including accelerations for evaluating objective functions of neighboring solutions; an improved nearest-neighbor-based constructive heuristic; an improved sweep-based constructive heuristic; an improved destruction procedure; and a simulated annealing type of acceptance criterion is proposed. At last, a series of comparative experiments are implemented based on some real-world instances from an electronic equipment manufacturing enterprise. The computational results demonstrate that the proposed IG algorithm has generated substantially better solutions than the existing algorithms in solving the problem under consideration.

在本文中，我们从矩阵制造车间解决了多室自动引导车辆调度（MC-AGVS）问题，该问题近年来引起了制造公司越来越多的关注。该问题旨在确定一种解决方案，以使包括旅行成本，服务成本和所涉及车辆成本在内的总成本降至最低。为此，首先构造一个混合整数线性规划模型。然后，提出了一种新颖的迭代贪婪算法，该算法包括用于评估相邻解的目标函数的加速度。改进的基于最近邻居的构造启发式算法；改进的基于扫描的建设性启发式算法；改进的销毁程序；提出了一种模拟退火验收准则。最后，基于电子设备制造企业的一些实际实例，进行了一系列比较实验。计算结果表明，提出的IG算法在解决所考虑的问题上比现有算法产生了更好的解决方案。