Scheduling method of automatic guided vehicle (AGV) optimal control time
A scheduling method and time technology, applied in data processing applications, forecasting, calculations, etc., can solve problems affecting the efficiency of material transportation and less overall waiting time.
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Embodiment 1
[0028] The embodiment of the present invention provides a scheduling method of AGV optimal control time, such as figure 1 As shown, the method includes:
[0029] Step 101, searching for basic units in the map model of the dispatching system, and dynamically generating a closed basic unit model based on the entire dispatching system model;
[0030] Step 102, for each basic unit, determine the AGVs passing through the central node and their sequence according to the weights of the edges formed by the central node and the primary and secondary nodes in the basic unit.
[0031] Further, the basic unit includes:
[0032] A central node, all first-level nodes directly connected to the central node, and all second-level nodes directly connected to these first-level nodes.
[0033] Further, the weight of the edge is the time required for the AGV to pass the edge at a normal speed.
[0034] Further, according to the weight of the edge formed by the central node and the primary and s...
Embodiment 2
[0044] The embodiment of the present invention provides a scheduling method of AGV optimal control time, such as figure 1 As shown, the method includes:
[0045] (1) Let N O Indicates the collection of AGV occupied nodes waiting for the delay. no c Indicates the node that the AGV is waiting to occupy, and all delayed AGVs pass through this node. The purpose of this method is to determine the AGV waiting for the delay to pass through node n c order of. The edge in the model is formed between two adjacent nodes, and the weight on the edge is described by the time required for the AGV to pass the edge at a normal speed. Edges and nodes constitute the scheduling map model of AGV, and AGV is abstracted as a point without size. The state of the system is represented by the state of all nodes in the map. Nodes that are not occupied by the AGV are described as 0, and those that are occupied are described as 1. As the position of the AGV node in the map is constantly changing, th...
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