Multi-vehicle-type collaborative sorting and scheduling method based on behavior dependency graph

Abstract

The invention discloses a multi-vehicle-type collaborative sorting and scheduling method based on a behavior dependency graph. The method comprises the following steps: acquiring a warehouse map, orders, starting positions and current states of sorting vehicles and carrying vehicles; according to the orders, the warehouse map and the current states of the sorting vehicles and the carrying vehicles, order tasks are allocated for the corresponding sorting vehicles and the carrying vehicles, and according to the order tasks of the vehicles, the optimal paths of the corresponding sorting vehicles and the carrying vehicles are determined and obtained; judging whether the optimal paths of the corresponding sorting vehicles and carrying vehicles have conflicts or not, and if yes, adding constraint conditions until an optimal allocation result and an optimal path of a conflict-free path are obtained; according to the optimal allocation result of the conflict-free path and the optimal path, carrying vehicles and sorting vehicles with allocation tasks are traversed, and a behavior dependence graph is constructed; and setting tangency points according to the behavior dependency graph, deleting all nodes behind the nodes corresponding to the tangency points, and starting next planning. And the sorting scheduling efficiency is effectively improved.

Description

technical field [0001] The invention belongs to the field of intelligent three-dimensional warehouse sorting and scheduling, in particular to a multi-vehicle cooperative sorting and scheduling method based on a behavior dependency graph. Background technique [0002] The system involved in the invention is a multi-model collaborative sorting and scheduling system based on a rolling time window, wherein the intelligent three-dimensional warehouse is divided into three layers, and each layer is placed with a plurality of high-level shelves to store small and medium-sized parts, and there are multiple sorting vehicles and transportation at the same time. car. Since a complete set of parts and components is required at the back end of the warehouse, a sorting vehicle and a truck are involved to complete the entire order task collaboratively. All the required parts are placed in the sorting car frame by the robot arm on the truck. [0003] Focusing on the above scenario require...

AI Technical Summary

Problems solved by technology

At present, more scholars are studying the single module of the intelligent three-dimensional warehouse sorting and dispatching system. The Genetic Algorithm is used to study the optimization problem of the fixed shelf picking operation path in the automated three-dimensional warehouse. The above research only considers the multi-vehicle path planning module alone.

Some scholars have established AGV running time models under various AGV (Automated Guided Vehicle) scheduling rules, and used traditional heuristic algorithms to solve the problem; some scholars have proposed the application of queuing and simulation models to distinguish key performance parameters and compare Different scheduling rule methods, the above research only considers the multi-vehicle scheduling module

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