A Path Optimization Method Based on the Evolutionary Mechanism of Bird Species

Abstract

The invention discloses a route optimizing method based on the evolutionary mechanism of birds. The method comprises randomly generating a plurality of feasible routes, wherein every route corresponds to the chromosomes of a bird, every node of the route corresponds to one gene on the chromosomes, the length of the gene is that of the rout, and the sequence of the genes is the sequence of the route nodes; determining the consumption required for passing through the feasible routes as adaptability functions; according to the amount of the consumption for passing through every feasible route, sorting and classifying the feasible routes; computing the number of the feasible routes of a promiscuous mating type, randomly regenerating a certain proportion of new feasible routes to substitute the feasible routes belonging to the promiscuous mating type; performing breeding reconstitution on every feasible route according to the species evolutionary model the feasible route belongs to, and after breeding reconstitution is completed, comparing the route lengths between parent individuals and offspring individuals, retaining the feasible routes with low consumption; performing repeated iteration under reaching a set iteration time threshold, obtaining a plurality of the feasible routes; selecting the route with the lowest consumption from the obtained feasible routes as the optimized route.

Description

technical field [0001] The invention relates to the field of network path optimization, and more specifically, to a path optimization method based on the evolution mechanism of bird species. Background technique [0002] The shortest path problem is the most basic problem in network optimization. It is widely used in the routing allocation of multi-hop networks and in accident repair, traffic command, GPS navigation and other industrial applications. The fast path optimization algorithm can make the system fully Use network resources to meet customer needs. [0003] (1) To solve the non-negative problem of the single-source shortest path, the most classic method is the Dijkstra algorithm. The Dijkstra algorithm is also called the single-source shortest path. It can find the shortest path from a vertex to all reachable vertices. The main feature is that the starting point is the center and expands outward layer by layer until it reaches the end point. The advantage of Dijks...

AI Technical Summary

Problems solved by technology

There are two main disadvantages of this method: one is that the algorithm’s ability to explore new spaces is limited, and it is easy to converge to a local optimal solution

The second is that the algorithm belongs to the random algorithm, which requires multiple calculations, the reliability of the result is poor, and the solution cannot be obtained stably.

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