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Proceedings Paper

Application of hybrid artificial fish swarm algorithm based on similar fragments in VRP
Author(s): Jinnuo Che; Kang Zhou; Xueyu Zhang; Xin Tong; Lingyun Hou; Shiyu Jia; Yiting Zhen
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Paper Abstract

Focused on the issue that the decrease of convergence speed and the precision of calculation at the end of the process in Artificial Fish Swarm Algorithm(AFSA) and instability of results, a hybrid AFSA based on similar fragments is proposed. Traditional AFSA enjoys a lot of obvious advantages in solving complex optimization problems like Vehicle Routing Problem(VRP). AFSA have a few limitations such as low convergence speed, low precision and instability of results. In this paper, two improvements are introduced. On the one hand, change the definition of the distance for artificial fish, as well as increase vision field of artificial fish, and the problem of speed and precision can be improved when solving VRP. On the other hand, mix artificial bee colony algorithm(ABC) into AFSA - initialize the population of artificial fish by the ABC, and it solves the problem of instability of results in some extend. The experiment results demonstrate that the optimal solution of the hybrid AFSA is easier to approach the optimal solution of the standard database than the other two algorithms. In conclusion, the hybrid algorithm can effectively solve the problem that instability of results and decrease of convergence speed and the precision of calculation at the end of the process.

Paper Details

Date Published: 8 March 2018
PDF: 11 pages
Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 106111L (8 March 2018); doi: 10.1117/12.2288191
Show Author Affiliations
Jinnuo Che, Wuhan Polytechnic Univ. (China)
Kang Zhou, Wuhan Polytechnic Univ. (China)
Xueyu Zhang, Wuhan Polytechnic Univ. (China)
Xin Tong, Wuhan Polytechnic Univ. (China)
Lingyun Hou, Wuhan Polytechnic Univ. (China)
Shiyu Jia, Wuhan Polytechnic Univ. (China)
Yiting Zhen , Wuhan Polytechnic Univ. (China)


Published in SPIE Proceedings Vol. 10611:
MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Nong Sang; Jie Ma; Zhong Chen, Editor(s)

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