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Layered heterogeneous dynamic particle swarm optimization algorithm

A particle swarm optimization and particle swarm technology, applied in computing, data processing applications, forecasting, etc., can solve problems such as slow convergence speed and premature algorithm, achieve fast convergence speed, enhance information interaction capabilities, improve local development capabilities and seek The effect of optimal efficiency

Inactive Publication Date: 2018-01-12
HARBIN ENG UNIV
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Problems solved by technology

This improved method can balance the local search ability and global search ability of the algorithm itself, and solves the shortcomings of the algorithm that is easy to "premature" and slow convergence due to the simple information sharing mechanism between particles.

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  • Layered heterogeneous dynamic particle swarm optimization algorithm
  • Layered heterogeneous dynamic particle swarm optimization algorithm
  • Layered heterogeneous dynamic particle swarm optimization algorithm

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Embodiment Construction

[0041] The present invention will be further described below. The following examples are only used to illustrate the technical solutions of the present invention more clearly, but not to limit the protection scope of the present invention.

[0042] The present invention proposes a multi-layer heterogeneous dynamic particle swarm optimization algorithm (MHPSO), which focuses on establishing the vertical interaction between multiple layers. Such as figure 1 As shown, the particle swarm is divided into 6 levels, each layer contains the same number of particles, and the number displayed by each particle represents its level. At each iteration, the particles are sorted according to their current fitness values ​​and assigned to different levels in turn. The smaller the fitness value of the particle, the higher the level it is in. In the algorithm, a particle is attracted by the particles in its immediate upper layer, the particles in its immediate upper layer are its attracting p...

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Abstract

The invention provides a multi-layer heterogeneous dynamic particle swarm optimization method for overcoming the defects in the prior art. According to the algorithm, the particle swarm topology structure is set to be of a multi-level structure, meanwhile, the concept of attraction particles is introduced in the process of updating the speed of the particles, the influence of the attraction particles around the particles on the particles is considered, and the speed updating formula of the particles is improved. According to the improved mode, the local searching capability and the global searching capability of the algorithm itself can be balanced., and the defects that an algorithm is premature and the convergence speed is low due to the fact that the information sharing mechanism between the particles is simple is well overcome. The particle swarm optimization algorithm has the beneficial effects that compared with a traditional particle swarm optimization algorithm, the convergencespeed is high, the information interaction capability between the particles is enhanced, and the local development capability and the optimizing efficiency of the algorithm are improved.

Description

technical field [0001] The invention relates to the technical field of computer applications, in particular to a layered heterogeneous dynamic particle swarm optimization algorithm. Background technique [0002] The optimization problem is an old subject, whether it is the microcosm or the macrocosm, the optimization problem is ubiquitous. The optimization problem is that for a certain problem, if there are many alternative solutions, it is necessary to determine the specific performance requirements and choose one of the multiple solutions to maximize or minimize the determined performance requirements. [0003] Since the optimization problem was proposed, people have proposed various methods for solving the optimization problem, and the research on the solution of the optimization problem has never stopped. These methods are mainly divided into two categories: the first category is to use the idea of ​​analysis, one of the methods The characteristic is to use the properti...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
Inventor 徐东姬少培孟宇龙张子迎王磊王岩峻张朦朦张玲玲李贤吕骏
Owner HARBIN ENG UNIV
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