Electric power communication network operation and maintenance work order scheduling method based on Hopfield neural network
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A power communication network and neural network technology, applied in the field of power communication network operation and maintenance work order scheduling, can solve problems such as complex calculations, inability to obtain optimal solutions, and failure to consider human factors constraints
Inactive Publication Date: 2020-05-26
GUANGDONG POWER GRID CO LTD +1
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[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
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[0102] Example 1
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[0103] like Figure 1 to Figure 7 Shown is a first embodiment of a Hopfield neural network-based power communication network operation and maintenance work order scheduling method, including the following steps:
[0104] S1. Analyze the requirements of operation and maintenance tasks in the power communication network and the capabilities of operation and maintenance personnel, and determine several factors that affect work order scheduling;
[0105] S2. Use fuzzy analytic hierarchy process to analyze several factors affecting work order scheduling, obtain the weight of each layer, and then obtain the coefficient matrix;
[0106] S3. According to the application scenario of assigning several tasks to several operation and maintenance personnel in the power communication network, establish constraints between the tasks and the operation and maintenance personnel, and then obtain the energy function;
[0107] S4. Use the Hopfield neural network to construct the maintenance task...
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[0162] Example 2
[0163] This embodiment is similar to Embodiment 1, except that, in this embodiment, the specific steps of step S3 are as follows:
[0164] S31. Establish an energy function according to the constraints between the task and the operation and maintenance personnel and the original formula of the neural network;
[0165] S32. Solve the total energy function according to the energy function.
[0166] In step S31, the constraints between the task and the operation and maintenance personnel include:
[0167] Constraint A: Each task can only be completed by one operation and maintenance personnel;
[0168] Constraint B: Each operation and maintenance personnel can only complete one task at a time;
[0169] Constraint C: Each task must be assigned to an operation and maintenance personnel, so all tasks and corresponding operation and maintenance personnel will form a pairing relationship;
[0170] Constraint D: At least two tasks are assigned to at least two ope...
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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...
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