Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem
This is an incremental improvement for researchers in optimization and computational intelligence, offering enhanced solutions to a classic combinatorial problem.
The paper tackled the Traveling Salesman Problem by using an enhanced Self-Organizing Map method to provide suboptimal solutions, with hyperparameter tuning to identify critical features, resulting in consistent improvements in benchmark results.
Using an enhanced Self-Organizing Map method, we provided suboptimal solutions to the Traveling Salesman Problem. Besides, we employed hyperparameter tuning to identify the most critical features in the algorithm. All improvements in the benchmark work brought consistent results and may inspire future efforts to improve this algorithm and apply it to different problems.