A collaborative neurodynamic optimization algorithm to traveling salesman problem
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 reform...
| Published in: | Complex & Intelligent Systems |
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| Main Authors: | , , , , , |
| Format: | Article |
| Language: | English |
| Published: |
Springer
2022-10-01
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-022-00884-6 |
| Summary: | 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. |
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| ISSN: | 2199-4536 2198-6053 |