Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 9
2694-2697

Hybrid path planning algorithm based on genetics and ant colony in DEM

Wu Xiaoniana,b
Xi Yu'angb
Zhang Runlianb,c
a. Guangxi Key Laboratory of Trusted Software, b. Guangxi Key Laboratory of Cryptography & Information Security, c. Guangxi Colleges Key Laboratory of Cloud Computing & Complex Systems, Guilin Guangxi 541004, China
DOI: 10.19734/j.issn.1001-3695.2019.04.0133

Abstract

The existing heuristic algorithm has low efficiency in the DEM path planning because of the large amount of data. In order to solve this problem, this paper proposed a hybrid path planning algorithm based on genetic algorithm and ant colony algorithm. In the genetic process, the algorithm constructed the selection factor in the initial population generation stage, which made the searched node more incline to the end direction and improved the efficiency of the initial population generation. And the algorithm restricted the variation interval of the mutation node during the mutation process to avoid the path break point. In the ant colony optimization process, according to the path information generated by the genetic process, it adopted the adaptive pheromone initialization and updated strategies to improve the algorithm search efficiency. Simulation experiments show that the hybrid algorithm can search the qualified path efficiently under the rule grid DEM.

Foundation Support

广西自然科学基金资助项目(2018GXNSFAA294036,2018GXNSFAA138116)
广西可信软件重点实验室基金资助项目(kx201622)
广西密码学与信息安全重点实验室项目(GCIS201705,GCIS201623)
广西高校云计算与复杂系统重点实验室项目(YF16205)
广西研究生教育创新计划资助项目(YCSW2018138,2017YJCX26)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.04.0133
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 9
Section: Algorithm Research & Explore
Pages: 2694-2697
Serial Number: 1001-3695(2020)09-026-2694-04

Publish History

[2020-09-05] Printed Article

Cite This Article

武小年, 奚玉昂, 张润莲. DEM中基于遗传与蚁群的混合路径规划算法 [J]. 计算机应用研究, 2020, 37 (9): 2694-2697. (Wu Xiaonian, Xi Yu'ang, Zhang Runlian. Hybrid path planning algorithm based on genetics and ant colony in DEM [J]. Application Research of Computers, 2020, 37 (9): 2694-2697. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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