An efficient improved particle swarm optimization based on prey behavior of fish schooling

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.

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