Application of K-means and Genetic Algorithm for MTSP
Keywords:
MTSP, Genetic Algorithm, Cluster Division, K-meansAbstract
This article implements a combination of K-means and genetic algorithms to solve the Multiple Traveling Salesman Problem (MTSP) while avoiding intersections between the paths of traveling salesmen. There are several objectives within this issue, including finding the shortest path for each route and determining the optimal number of cluster divisions. In this research, we attempt to combine the K-means algorithm and genetic algorithm to address the MTSP with cluster divisions. The study involves dividing destinations using K-means and applying the Genetic Algorithm to these clusters. The results demonstrate that the combination of Genetic Algorithm and cluster division significantly contributes to efficient travel route planning. Clustering enables the grouping of destinations with similar geographic characteristics, leading to more optimal routes. In future research, optimizing parameters and integrating other methods can be explored to enhance the solution for travel planning.
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