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Route optimization method based on chaos searching and artificial immune algorithm

An artificial immune algorithm and chaotic search technology, applied in the field of communication networks, can solve problems such as uncertain single optimization results and low efficiency of solution generation

Active Publication Date: 2016-06-22
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to provide a routing optimization method based on chaotic search and artificial immune algorithm, which is used to solve the defects of low generation efficiency of feasible path solution and uncertain single optimization result in the prior art

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  • Route optimization method based on chaos searching and artificial immune algorithm
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  • Route optimization method based on chaos searching and artificial immune algorithm

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Embodiment Construction

[0044] The preferred embodiments will be described in detail below in conjunction with the accompanying drawings. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

[0045] figure 1 Be the flow chart of the present invention, figure 2 It is a network topology diagram used in the embodiment of the present invention. The network is the Italian national network, and the numbers on the links represent the unitized lengths between nodes. Combine below figure 1 and figure 2 Specific embodiments of the present invention will be described.

[0046] Step 1 (population initialization):

[0047] The objective function of multi-constraint routing optimization in this embodiment is f=αf 1 +βf 2 +γf 3 , where f 1 is the path length, f 2 is the variance of the network service layer load when the service is transmitted along the path, f 3 is the variance of the network transport layer...

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Abstract

The invention discloses a route optimization method based on chaos searching and an artificial immune algorithm in the technical field of communication networks. The route optimization method is used for solving the problems of low route generation efficiency and uncertain single optimization result when the traditional intelligent optimization algorithm is used for solving a multi-target route optimization problem. The route optimization method comprises the steps of: generating a plurality of paths as initial antibody species of the artificial immune algorithm by utilizing chaos searching and a dynamic adjacency matrix; and utilizing the artificial immune algorithm to acquire an optimal route. The route optimization method further comprises the main steps of: cloning superior antibodies and inoculating clonal antibodies with dynamic vaccine; carrying out mutation operation on the clonal antibodies inoculated with the vaccine; carrying out free mutation operation on the secondary superior antibodies; and integrating the superior antibodies, the mutated clonal antibodies inoculated with the vaccine and the secondary superior antibodies after free mutation into a new generation of antibody species. The route optimization method is high in route generation efficiency, replaces a radon probability value with a chaos search value, and has the advantages of fast optimization searching speed and stable single output result.

Description

technical field [0001] The invention belongs to the technical field of communication networks, in particular to a routing optimization method based on chaos search and artificial immune algorithm. Background technique [0002] With the continuous increase of network functions, routing optimization under single constraint conditions can no longer meet users' requirements for network service quality. The multi-constraint routing optimization problem is an NP-complete problem, which cannot be solved accurately in polynomial time, so many researchers use intelligent evolutionary algorithms to solve the multi-constraint routing optimization problem. MehdiGhatee uses a hybrid genetic algorithm to solve multi-commodity flow routing problems, which improves channel utilization and reduces delay and blocking rates; Liu Xin, Li Fei and others use quantum genetic algorithms to solve anycast QoS routing problems, making network resources The utilization is more reasonable and reduces t...

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Application Information

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IPC IPC(8): H04L12/721G06N3/12
Inventor 樊冰吴润泽闫江毓唐良瑞
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)