Computer Science ›› 2017, Vol. 44 ›› Issue (4): 281-287.doi: 10.11896/j.issn.1002-137X.2017.04.058

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New Improved Artificial Fish Swarm Algorithm

LIU Dong-lin and LI Le-le   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Aiming at the problems of easy to fall into the local optimum value,converging slowly in the later period and low solving accuracy that artificial fish swarm algorithm(AFSA) have,a new improved artificial fish algorithm (IAFSA) was proposed. Firstly,the new algorithm uses chaos transform to initialize the position of individual fish,and the fish is more evenly distributed in the specified area within the region,that keeps the fish population diversity,and it is conducive to global convergence.Secondly,the artificial fish with different function values in foraging behavior take different visual,and it not only improves the searching speed but also reduces the possibility of the artificial fish falling into local optimum.Finally,according to the relationship between physical and the activity,a physical transformation mo-del is construct,and the physical of artificial fish become weaken in the late stage of the algorithm,reducing the step timely is very important,which can improve the convergence speed and the accuracy of the algorithm.The algorithm is verified by standard test function and TSP of 14 cities,and the experimental results show that the improved algorithm has faster convergence speed and higher precision than the basic artificial fish swarm algorithm.

Key words: Sartificial fish swarm algorithm,Chaos transform,Foraging behavior,Physical transformation model

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