Method for selecting optimal path of power distribution and utilization communication network based on genetic algorithm

Abstract

The invention discloses a method for selecting the optimal path of a power distribution and utilization communication network based on the genetic algorithm. The method is characterized by including the following steps that first, a unidirectional topology network is established; second, the population is initialized through binary coding; third, the number of iterations is set; fourth, selecting operation is performed; fifth, crossover operation is performed; sixth, mutation operation is performed; seventh, judgment is performed; eighth, the optimal path is output. On the basis of meeting the constraint conditions, the optimal path is efficiently found so that the search efficiency can be improved and the search complexity can be reduced.

Description

technical field [0001] The invention relates to a method for finding an optimal path with node constraint conditions in a power distribution communication network, specifically a method for selecting the optimal path of a power distribution communication network based on a genetic algorithm. Background technique [0002] The current networking method of the power distribution communication network is relatively complicated. When a certain section of cable is interrupted, it is necessary to select an appropriate path to connect to the main network. The current method is to manually select the path. The path in the middle is more complicated and difficult to choose. Large, it often takes a long time to debug to achieve connectivity, and the path selected is not necessarily the shortest path, which also causes a waste of resources, and at the same time cannot reach the minimum attenuation rate, resulting in a long interruption of the optical path , which has a certain impact on...

AI Technical Summary

Problems solved by technology

[0002] The current networking method of the power distribution communication network is relatively complicated. When a certain section of cable is interrupted, it is necessary to select an appropriate path to connect to the main network. The current method is to manually select the path. The path in the middle is more complicated and difficult to choose. It often takes a long time to debug to achieve connectivity, and the path selected is not necessarily the shortest path, which also causes a waste of resources, and at the same time cannot reach the minimum attenuation rate, resulting in a long interruption of the optical path , which has a certain impact on the collection of power distribution business data

[0003] The current algorithms for solving the optimal path problem, such as: Dijkstra algorithm, Johnson algorithm, traditional genetic algorithm, etc., cannot directly solve the optimal path problem with node constraints

The Dijkstra algorithm and Johnson algorithm can also solve the optimal path problem of node constraints through improvement, but when there are many nodes in the network topology, the search efficiency of this type of algorithm is low, and the efficiency becomes even lower after the improvement.

When the traditional genetic algorithm calculates the optimal path with node constraints, because of the cross-mutation of population individuals, it cannot guarantee that the final output optimal path is the optimal path that satisfies the node constraints

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