Complex & Intelligent Systems (Oct 2022)

A collaborative neurodynamic optimization algorithm to traveling salesman problem

  • Jing Zhong,
  • Yuelei Feng,
  • Shuyu Tang,
  • Jiang Xiong,
  • Xiangguang Dai,
  • Nian Zhang

DOI
https://doi.org/10.1007/s40747-022-00884-6
Journal volume & issue
Vol. 9, no. 2
pp. 1809 – 1821

Abstract

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Abstract This paper proposed a collaborative neurodynamic optimization (CNO) method to solve traveling salesman problem (TSP). First, we construct a Hopfield neural network (HNN) with $$n \times n$$ n × n neurons for the n cities. Second, to ensure the convergence of continuous HNN (CHNN), we reformulate TSP to satisfy the convergence condition of CHNN and solve TSP by CHNN. Finally, a population of CHNNs is used to search for local optimal solutions of TSP and the globally optimal solution is obtained using particle swarm optimization. Experimental results show the effectiveness of the CNO approach for solving TSP.

Keywords