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Volumn 35, Issue 1, 2014, Pages 1-6

Improved artificial fish-swarm algorithm based on adaptive vision for solving the shortest path problem

Author keywords

Adaptive vision; Ant colony optimization; Artificial fish swarm algorithm; Shortest path

Indexed keywords


EID: 84894553985     PISSN: 1000436X     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1000-436x.2014.01.001     Document Type: Article
Times cited : (29)

References (10)
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  • 3
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    • GAN R W. Research on ant colony optimization and its application[D]. Guangzhou: Sun Yat-sen University, 2009.
    • (2009)
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  • 5
    • 77954521580 scopus 로고    scopus 로고
    • Research on the shortest path problem based on an improved ant colony algorithm
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  • 6
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  • 7
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    • ZHEN G R. Vehicle congestion scheduling scheme based on a mixed artificial fish-swarm algorithm[J]. Computer Simulation, 2012, 29(6): 328-331.
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  • 8
    • 0036881676 scopus 로고    scopus 로고
    • An optimization mode based on Autonomous: fish-swarm algorithm
    • LI X L, SHAO Z J, QIAN J X. An optimization mode based on Autonomous: fish-swarm algorithm[J]. Systems Engineering Theory and Practice, 2002, 22(11):32-38.
    • (2002) Systems Engineering Theory and Practice , vol.22 , Issue.11 , pp. 32-38
    • Li, X.L.1    Shao, Z.J.2    Qian, J.X.3
  • 9
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    • LI X L. A new type of intelligent optimization method: artificial fish-swarm algorithm[D]. Hangzhou: Zhejiang University, 2003.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.