Electric power communication network operation and maintenance work order scheduling method based on Hopfield neural network

Abstract

The invention relates to the technical field of operation and maintenance work order scheduling, in particular to an electric power communication network operation and maintenance work order scheduling method based on a Hopfield neural network, which comprises the following steps: S1, analyzing the requirements of operation and maintenance tasks and the capabilities of operation and maintenance personnel in an electric power communication network, and determining a plurality of factors influencing work order scheduling; S2, analyzing a plurality of factors influencing work order scheduling byutilizing a fuzzy analytic hierarchy process to obtain the weight of each layer, and further obtaining a coefficient matrix; S3, establishing constraint conditions between the tasks and the operationand maintenance personnel according to the application scenarios in which the tasks are allocated to the operation and maintenance personnel in the power communication network, and then obtaining an energy function; and S4, constructing a power communication network maintenance task scheduling model by using a Hopfield neural network, and obtaining optimal matching when a plurality of tasks are allocated to a plurality of operation and maintenance personnel according to the coefficient matrix and the energy function. According to the invention, the quality of work order allocation and the utilization rate of resources can be improved, and reasonable scheduling of operation and maintenance work orders under multi-resource constraints is realized.

Description

technical field [0001] The present invention relates to the technical field of operation and maintenance work order scheduling, and more specifically, to a Hopfield neural network-based operation and maintenance work order scheduling method for electric power communication networks. Background technique [0002] With the gradual improvement of the construction of my country's electric power communication network, the number of access devices is increasing, and the number and types of services carried are also increasing. my country has a vast territory and the grid nodes are widely distributed. Some base stations are located in remote locations and the environment is harsh. It is unrealistic to assign resident operation and maintenance personnel to each grid node. It is of great significance to effectively meet the maintenance requirements of faults and ensure the normal operation of power communication services by formulating an efficient and reasonable work order allocation...

AI Technical Summary

Problems solved by technology

[0004] At present, there is an on-site operation and maintenance work order scheduling management method based on task matching for electric power communication, but this method cannot obtain the optimal solution when multiple tasks are assigned to multiple operation and maintenance personnel; there is also a virus propagation algorithm-based method. On-site operation and maintenance work order scheduling method of electric power communication network, but this method is complex in calculation and consumes a lot of resources, and is not suitable for complex and large-scale multi-task electric power communication systems; there are also real-time task scheduling algorithms based on task dynamic priority, but This method does not take into account human factor constraints, so it is not well suited for power communication systems

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