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Rapid Physarum Algorithm for shortest path problem

Zhang,X, Zhang,Y, Zhang,Z, Mahadevan,S, Adamatzky,A and Deng,Y 2014, Rapid Physarum Algorithm for shortest path problem, Applied Soft Computing Journal, vol. 23, pp. 19-26, doi: 10.1016/j.asoc.2014.05.032.

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Title Rapid Physarum Algorithm for shortest path problem
Author(s) Zhang,X
Zhang,Y
Zhang,ZORCID iD for Zhang,Z orcid.org/0000-0002-8721-9333
Mahadevan,S
Adamatzky,A
Deng,Y
Journal name Applied Soft Computing Journal
Volume number 23
Start page 19
End page 26
Total pages 8
Publisher Elsevier
Place of publication Amsterdam, Netherlands
Publication date 2014-10
ISSN 1568-4946
Keyword(s) Heuristic rule
Physarum polycephalum
Rapid Physarum Algorithm
Shortest path problem
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
Computer Science
OPTIMIZATION ALGORITHM
AMEBOID ORGANISM
SLIME-MOLD
NETWORK
INTELLIGENCE
POLYCEPHALUM
COMPUTATION
NAVIGATION
ROBOT
Summary As shortest path (SP) problem has been one of the most fundamental network optimization problems for a long time, technologies for this problem are still being studied. In this paper, a new method by integrating a path finding mathematical model, inspired by Physarum polycephalum, with extracted one heuristic rule to solve SP problem has been proposed, which is called Rapid Physarum Algorithm (RPA). Simulation experiments have been carried out on three different network topologies with varying number of nodes. It is noted that the proposed RPA can find the optimal path as the path finding model does for most networks. What is more, experimental results show that the performance of RPA surpasses the path finding model on both iterations and solution time. © 2014 Elsevier B.V.
Language eng
DOI 10.1016/j.asoc.2014.05.032
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30071813

Document type: Journal Article
Collection: School of Information Technology
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