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Efficient improved FSPSO (Particle Swarm Optimization based on prey behavior of Fish Schooling)

A technology for improving particle swarms and fish swarms, applied in the field of evolutionary algorithms to achieve the effect of enhancing diversity and avoiding local optimal values

Inactive Publication Date: 2015-07-29
WUHAN UNIV
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Problems solved by technology

[0003] When the above algorithm optimizes complex high-dimensional multi-modular functions, it is still easy to fall into local optimum

Method used

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  • Efficient improved FSPSO (Particle Swarm Optimization based on prey behavior of Fish Schooling)
  • Efficient improved FSPSO (Particle Swarm Optimization based on prey behavior of Fish Schooling)
  • Efficient improved FSPSO (Particle Swarm Optimization based on prey behavior of Fish Schooling)

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Embodiment Construction

[0022] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0023] Assuming that the number of particles in the particle swarm optimization algorithm is n, the search space is D-dimensional, and the position and velocity of the i-th particle are x i and v i ,but:

[0024] x i =(x i1 ,...,x id ,...,x iD ) (1),

[0025] v i =(v i1 ,...,v id ,...,v iD ) (2);

[0026] The position of the particle with the best fitness in the population is recorded as:

[0027] P g =(P g1 ,P g2 ,...,P gD ) (3);

[0028] The best position of the solution space experienced by the i-th particle is:

[0029] P i =(P i1 ,P ...

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Abstract

The invention discloses an efficient improved FSPSO (Particle Swarm Optimization based on prey behavior of Fish Schooling). According to the efficient improved FSPSO, an intelligent behavior is simulated, and current globally-optimal particles search for current globally-superior positions through own optimal position information provided by a minority of other random particles. When fish schooling is attacked by other predators, weak fish which cannot escape quickly is eaten. The behaviors are simulated, weak particles close to current globally-worst particles are replaced with particles which are generated randomly, so that the diversity of the schooling is improved, and a local optimum can be effectively avoided by the FSPSO. The efficient improved FSPSO can be particularly applied to the solving process of complicated optimization problems such as function optimization and knapsack problems, traveling salesman problems, assembly line work problems and graph and image processing problems.

Description

technical field [0001] The invention belongs to the technical field of evolutionary algorithms, and relates to a particle swarm optimization algorithm, in particular to an efficient improved particle swarm algorithm based on the behavior of fish rushing for food. Background technique [0002] Particle Swarm Optimization (PSO) is a novel evolutionary algorithm proposed by Kennedy and Eberhart through the observation and research of certain social behaviors of birds. Since PSO has few setting parameters and is easy to implement, it can be used to solve a large number of complex optimization problems such as nonlinear, non-differentiable and multi-peak, and has been successfully applied to parameter optimization, feature extraction, traveling salesman problem, pattern recognition and many other fields. However, in complex optimization problems, the particle swarm optimization algorithm has premature convergence, and it is easy to fall into a local optimal solution. Angeline et...

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Application Information

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IPC IPC(8): G06N3/00
Inventor 何发智鄢小虎
Owner WUHAN UNIV
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