An improved method for solving conflict-free scheduling and routing of automated guided vehicles is proposed in this article, with promising results. This is achieved by reformulating the mathematical model of the problem, including several improvements and speedup strategies of an existing Benders decomposition method. A new heuristic is also presented that quickly yields high-quality solutions. Moreover, a real-large-scale industrial instance is solved using an open-source satisfiability module theories solver and a commercial constraint programming solver. According to the results, both of these general-purpose solvers can effectively solve the proposed models. Note to Practitioners —The problem of conflict-free routing and scheduling of automated guided vehicles (AGVs) in large-scale manufacturing systems has been an ever-present challenge for many AGV companies. Although these companies have developed rather efficient control policies and algorithms, retrofitting the existing heuristic to future’s denser, more complicated, and more demanding AGV layouts is not guaranteed to be easy. Furthermore, the installed system will not necessarily be as efficient as expected. Currently, it is common to use heuristics to allocate vehicles to orders and route them. There are also rules of thumbs to avoid collisions and deadlocks. However, with increasing demand for high-performance AGV solutions, it is of interest to employ optimization algorithms that handle the order allocation, scheduling, and routing in a more efficient way. In this article, we present an improved method to tackle this issue, with promising results. We have developed our work in collaboration with a Swedish AGV company, and we have investigated a real-large-scale industrial instance as our case study.

中文翻译：

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使用 CP/SMT 求解器进行 AGV 的调度和路由


本文提出了一种解决自动引导车无冲突调度和路径问题的改进方法，并取得了可喜的结果。这是通过重新表述问题的数学模型来实现的，包括对现有 Benders 分解方法的多项改进和加速策略。还提出了一种新的启发式方法，可以快速产生高质量的解决方案。此外，使用开源可满足性模块理论求解器和商业约束规划求解器来求解真实的大规模工业实例。根据结果​​，这两个通用求解器都可以有效地求解所提出的模型。从业者须知——大规模制造系统中自动引导车辆 (AGV) 的无冲突路由和调度问题一直是许多 AGV 公司面临的挑战。尽管这些公司已经开发出相当有效的控制策略和算法，但将现有的启发式技术改造为未来更密集、更复杂、要求更高的 AGV 布局并不容易。此外，安装的系统不一定像预期的那样高效。目前，通常使用启发式方法将车辆分配给订单并进行路线安排。还有避免冲突和死锁的经验法则。然而，随着对高性能 AGV 解决方案的需求不断增加，采用优化算法以更有效的方式处理订单分配、调度和路由是很有意义的。在本文中，我们提出了一种改进的方法来解决这个问题，并取得了可喜的结果。我们与一家瑞典 AGV 公司合作开发了我们的工作，并调查了一个真实的大型工业实例作为我们的案例研究。