Abstract
This paper studies the solution procedure to the problem of conflict-free route planning for automated guided vehicles for just-in-time delivery to minimize the earliness and tardiness of a specified delivery time while minimizing the total completion time. The characteristic of the problem is that a vehicle can have an idle time at any nodes considering dispatching of dynamic task arrivals. This problem is modeled by a time-space network where the pickup and delivery tasks are dynamically scheduled. A heuristic solution procedure is developed to derive a conflict-free routing problem such that earliness and tardiness penalties are minimized while the total completion time of each task is also minimized under dynamic task arrivals. The effectiveness of the proposed method is demonstrated by comparing the performance with Gurobi from computational results. The results show that the proposed method can obtain a better solution that is close to an optimal solution with significantly shorter computational time than that derived from Gurobi. The trade-off relationship between earliness/tardiness penalties and the total completion time is investigated in various situations. The effects of the interval of task assignment on the performance of earliness/tardiness and the total completion time are studied. The computational results show the conditions when the trade-off relationship can be obtained. <i>Note to Practitioners</i>—The multiple AGVs are used in public transportation and social systems with rapid development of artificial intelligence and optimization methods. The benefits of AGV affect the reduction of congestion, traffic police, legal services, and economic savings in the manufacturing and logistics industries. In order to satisfy the customer’s demands, it is requested to deliver the products just-in-time for the desired time without decreasing the total system performance. This paper presents the dispatching and conflict-free routing of AGVs for just-in-time transportation while minimizing the total completion time of the tasks. In many real factories with multiple production processes, the shortest time transportation may sometimes cause the congestions of AGVs waiting for handling or overstocked. Just-in-time transportation is required not only to reduce inventories but also to supply only when it is needed. Computational results show the situations when the just-in-time delivery and the minimization of the total completion time can be achieved.
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More From: IEEE Transactions on Automation Science and Engineering
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