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An Optimization Method of SNNs for Shortest Path Problem

  • Hong QuEmail author
  • Zhi Zeng
  • Changle Chen
  • Dongdong Wang
  • Nan Yao
Part of the Proceedings in Adaptation, Learning and Optimization book series (PALO, volume 1)

Abstract

In this paper we propose a new optimization method of integrate-and-fire neural model for shortest path problem and compare it with Dijkstra algorithm. The proposed algorithm improves the speed of path planning by parallel property of spike spreading in the network and makes efficiency independent from the number of connections of the network which is only related to the length of the shortest path in the network with determined number of edges. Mathematical analysis and simulations demonstrate that planing shortest path by utilizing connections between transmission time in integrate-and-fire model and edge weights is feasible. The comparisons with Dijkstra algorithm manifest that the new algorithm does have superiority in some application scenarios.

Keywords

Shortest path problem Spike spreading Integrate-and-fire model 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Hong Qu
    • 1
    Email author
  • Zhi Zeng
    • 1
  • Changle Chen
    • 1
  • Dongdong Wang
    • 1
  • Nan Yao
    • 1
  1. 1.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduP.R. China

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