Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem

TL;DR

This paper presents an improved Self-Organizing Map approach for solving the Traveling Salesman Problem, emphasizing hyperparameter tuning and consistent benchmark results to inspire future research.

Contribution

It introduces an enhanced SOM method with hyperparameter tuning, achieving improved solutions and providing insights for future algorithm development.

Findings

Consistent benchmark improvements over previous methods

Identification of critical hyperparameters for the algorithm

Potential for applying the approach to other problems

Abstract

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.