An amoeboid algorithm for shortest path in fuzzy weighted networks

Zhang, Yajuan, Zhang, Zili, Zhang, Xiaoge, Wei, Daijun and Deng, Yong 2012, An amoeboid algorithm for shortest path in fuzzy weighted networks, in CCDC 2012 : Proceedings of the 24th Chinese Control and Decision Conference, IEEE Industrial Electronics, Singapore, Singapore, pp. 3709-3713.

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Title An amoeboid algorithm for shortest path in fuzzy weighted networks
Author(s) Zhang, Yajuan
Zhang, Zili
Zhang, Xiaoge
Wei, Daijun
Deng, Yong
Conference name Chinese Control and Decision. Conference (24th : 2012 : Taiyun, China)
Conference location Taiyuan, China
Conference dates 23-25 May. 2012
Title of proceedings CCDC 2012 : Proceedings of the 24th Chinese Control and Decision Conference
Editor(s) [Unknown]
Publication date 2012
Conference series Chinese Control and Decision. Conference
Start page 3709
End page 3713
Total pages 5
Publisher IEEE Industrial Electronics
Place of publication Singapore, Singapore
Keyword(s) amoeboid algorithm
fuzzy numbers
physarum polycephalum
shortest path
Summary Taking the uncertainty existing in edge weights of networks into consideration, finding shortest path in such fuzzy weighted networks has been widely studied in various practical applications. In this paper, an amoeboid algorithm is proposed, combing fuzzy sets theory with a path finding model inspired by an amoeboid organism, Physarum polycephalum. With the help of fuzzy numbers, uncertainty is well represented and handled in our algorithm. What's more, biological intelligence of Physarum polycephalum has been incorporate into the algorithm. A numerical example on a transportation network is demonstrated to show the efficiency and flexibility of our proposed amoeboid algorithm.
ISBN 9781457720734
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
080110 Simulation and Modelling
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30049567

Document type: Conference Paper
Collection: School of Information Technology
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