A production workshop with mobile robots can be considered as a hybrid system consisting of a production system and a transportation one. Mobile robots are responsible for transferring production tasks among the machines of a production system and constitute a multi-robot transport system. It is highly coupled with a production system because of the interdependency that exists between production scheduling and mobile robot assignment. In this work, we study their integrated optimization problem for a mobile robot-based job shop with blocking properties. Its aim is to minimize total completion time as an objective function to improve overall operational efficiency. We consider the speed of a robot that varies according to whether it is loaded or not. We formulate this new problem into a mixed integer linear program to provide an algebraic description. Then, we propose a constraint programming method to solve it with high efficiency. The superiority of constraint programming over mixed integer linear programming in terms of the number of variables and constraints is analyzed. Numerous experiments on benchmark examples show that constraint programming can well handle the concerned problem. Under a one-hour time limit, it can exactly solve its instances while mixed integer linear programming cannot. Under a one-minute time limit, it obtains much better solutions than mixed integer linear programming and heuristic strategies, thus implying its high potential to be put into industrial applications. Note to Practitioners—The integration of mobile robots into production workshops has emerged as a pivotal strategy to enhance the operational efficiency of an advanced manufacturing system. This integration transforms the traditional job shop into a hybrid system, where mobile robots play a crucial role in transferring production tasks among machines. This brings a unique challenge to practitioners due to the intricate interdependencies between production scheduling and mobile robot assignment. The focus of our study is on the optimization of a mobile robot-based job shop to improve its overall operational efficiency. Our approach involves formulating this complex problem as a mixed-integer linear program, thereby providing a concise mathematical representation. We propose a constraint programming method to solve the problem efficiently. Through numerous experiments on benchmark examples, our findings indicate that the proposed constraint programming method can well solve the concerned problem given long or short solution time. This underscores its high potential for practical implementation in industrial scenarios.

中文翻译：

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多移动机器人运输与生产集成系统优化


具有移动机器人的生产车间可以被视为由生产系统和运输系统组成的混合系统。移动机器人负责在生产系统的机器之间转移生产任务，构成多机器人运输系统。由于生产调度和移动机器人分配之间存在相互依赖性，它与生产系统高度耦合。在这项工作中，我们研究了具有阻塞特性的基于移动机器人的作业车间的集成优化问题。其目标是以最小化总完成时间作为目标函数，以提高整体运营效率。我们考虑机器人的速度根据其是否装载而变化。我们将这个新问题表述为混合整数线性规划以提供代数描述。然后，我们提出了一种约束规划方法来高效地解决它。分析了约束规划相对于混合整数线性规划在变量和约束数量方面的优越性。对基准示例的大量实验表明，约束规划可以很好地处理所关注的问题。在一小时的时间限制下，它可以精确地解决其实例，而混合整数线性规划则不能。在一分钟的时间限制下，它获得了比混合整数线性规划和启发式策略更好的解决方案，这意味着其具有很高的工业应用潜力。从业者须知——将移动机器人集成到生产车间已成为提高先进制造系统运营效率的关键策略。 这种集成将传统的作业车间转变为混合系统，其中移动机器人在机器之间转移生产任务方面发挥着至关重要的作用。由于生产调度和移动机器人分配之间错综复杂的相互依赖关系，这给从业者带来了独特的挑战。我们研究的重点是优化基于移动机器人的作业车间，以提高其整体运营效率。我们的方法涉及将这个复杂问题表述为混合整数线性程序，从而提供简洁的数学表示。我们提出了一种约束规划方法来有效地解决该问题。通过对基准示例的大量实验，我们的研究结果表明，所提出的约束规划方法可以很好地解决给定长或短求解时间的相关问题。这凸显了其在工业场景中实际实施的巨大潜力。