Research on navigation of bidirectional A algorithm based on ant colony algorithm

To overcome the lengthy search time, massive space occupation, and overlong planned path of the traditional A* algorithm, this paper integrates the bidirectional search with the intelligent ant colony algorithm to obtain the heuristic function selection factor, and uses the factor to improve the eva...

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Veröffentlicht in:The Journal of supercomputing Jg. 77; H. 2; S. 1958 - 1975
Hauptverfasser: Chen, Yu-qiang, Guo, Jian-lan, Yang, Huaide, Wang, Zheng-qin, Liu, Hong-ling
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.02.2021
Springer Nature B.V
Schlagworte:
Algorithms
Ant colony optimization
Compilers
Computer Science
Deep Learning
Interpreters
Navigation
Parallel Computing in Biomed Sciences & Healthcare
Processor Architectures
Programming Languages
Searching
A algorithm
Heuristic function
Path planning
Ant colony algorithm (ACA)
Bidirectional search
ISSN:0920-8542, 1573-0484
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Zusammenfassung:To overcome the lengthy search time, massive space occupation, and overlong planned path of the traditional A* algorithm, this paper integrates the bidirectional search with the intelligent ant colony algorithm to obtain the heuristic function selection factor, and uses the factor to improve the evaluation function of the algorithm. The simulation results show that the improved algorithm achieved better dynamic navigation than the traditional A* algorithm both in search time and distance, featuring shorter path searching time and the algorithm running time. Therefore, the result of this research has effectively reduced the search time and enhanced the dynamic search.
Bibliographie:ObjectType-Article-1
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-020-03303-0