An Efficient Heuristic for the Traveling Salesman Problem Based on a Growing SOM-like Algorithm
A growing self-organizing (SOM) neural network, enhanced with a local search heuristic is proposed as an efficient traveling salesman problem solver. A ring structure of processing units is evolved in time with a Kohonen type adaptation dynamics together with a simple growing rule in the number of processing units. The result is a neural network heuristic for the TSP with a computational complexity of O(n 2), comparable to other reported SOM-like networks. The tour emerging from the SOM network is enhanced by the application of a simple greedy 2-Opt local search. Experiments over a broad set of TSP instances are carried out. The experimental results show a solution accuracy equivalent to that of the best SOM based heuristics reported in the literature.
KeywordsTravel Salesman Problem Travel Salesman Problem Direct Neighbor Local Search Heuristic Insertion Strategy
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