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Method for improving salp swarm algorithm

A salp group and salp technology, applied in calculation, calculation model, instrument, etc., can solve the problems of poor population diversity and inability to perform precise search, achieve high solution accuracy, and enhance the effect of local search ability

Pending Publication Date: 2020-04-17
TIANJIN UNIV
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Problems solved by technology

[0003] The purpose of the present invention is to provide a method for improving the salp group algorithm in order to overcome the deficiencies in the prior art, aiming at the shortcomings of the salp group algorithm that cannot be accurately searched in the later stage of iteration, and the population diversity is relatively poor. algorithm improvement

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  • Method for improving salp swarm algorithm
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  • Method for improving salp swarm algorithm

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specific Embodiment approach

[0029] By studying the principle of the salp swarm algorithm, it is found that due to the unconstrained location update search range and the small influence weight of elite individuals, the salp swarm algorithm cannot perform a very accurate search in the late iteration, and the followers cannot assist the individual position very well. renew. Therefore, the improvement idea of ​​the present invention is considered from two aspects: aiming at the problem that the search range of the salp swarm algorithm is not limited in the leader update stage, adding an attenuation factor to enhance the local development ability in the later stage of iteration; aiming at the limitation of follower position update Introducing a dynamic learning strategy to improve the global exploration ability. See figure 1 , the specific implementation is as follows:

[0030] Step 1: Suppose there are 50 individuals in the salp group, moving in a 30-dimensional search space, and the upper and lower bounda...

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Abstract

The invention discloses a method for improving a salp swarm algorithm, and aims to improve the salp swarm algorithm to overcome the defects that the salp swarm algorithm cannot perform accurate searchin the later stage of iteration, is poor in population diversity and the like. By adding an attenuation factor, the search range is flexibly controlled and the algorithm convergence speed is increased, and by introducing a dynamic learning strategy, the assistance effect of a follower on optimization is enhanced, higher convergence precision of the algorithm is achieved, and the optimization performance of the salp swarm algorithm is improved. The convergence precision and the convergence speed of the improved salp swarm algorithm are greatly improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a novel swarm intelligence algorithm. Background technique [0002] The salp swarm algorithm is a new swarm intelligence optimization algorithm proposed by Australian scholar Mirjalili in 2017. This algorithm simulates the group foraging behavior of marine animal salps. The mechanism is simple and easy to understand, easy to operate, and easy to implement. A research hotspot of a large number of researchers. Today, the algorithm has been widely used in practical problems. The salp swarm algorithm also has disadvantages such as inability to perform precise search in the later stage of iteration and poor population diversity, which limits the local development ability and global exploration ability of the algorithm. Compared with other intelligent optimization algorithms, the optimal solution strategy of the salp swarm algorithm needs to be improved to further imp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 蔺悦陈雷
Owner TIANJIN UNIV
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