Hybrid Artificial Fish Algorithm to Solve TSP Problem

被引：5

作者：

Cheng, Chun-ying ^{[1
]}

Li, Hai-Feng ^{[2
]}

Bao, Chun-Hua ^{[1
]}

机构：

[1] Inner Mongolia Univ Nationalities, Coll Comp Sci & Technol, Tongliao 028043, Peoples R China

[2] Inner Mongolia Coal Ind Tech Sch, Comp Educ Dept, Tongliao 028021, Peoples R China

来源：

PROCEEDINGS OF THE 6TH INTERNATIONAL ASIA CONFERENCE ON INDUSTRIAL ENGINEERING AND MANAGEMENT INNOVATION, VOL 2: INNOVATION AND PRACTICE OF INDUSTRIAL ENGINEERING AND MANAGMENT | 2016年

关键词：

Crossover operator; Hybrid algorithm; Improved behavior; TSP problem;

D O I：

10.2991/978-94-6239-145-1_27

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Based on the research of the Artificial Fish Swarm Algorithm, this paper put forward an improved hybrid artificial fish algorithm which involves improved preying behavior and improved swarming behavior. Then the performance of the algorithm is improved through introducing genetic crossover operator and a better scope of vision function so as to solve TSP problem. Through the simulation experiment and comparison of improved artificial fish algorithm of literature, the results show that the improved hybrid algorithm in convergence performance and the solution accuracy and convergence rate of the improved artificial fish algorithm is superior to literature.

引用

页码：275 / 285

页数：11

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