Reducing the time needed to solve a traveling salesman problem by clustering with a Hierarchy-based algorithm
Abstract
In this study, we compare a cluster-based whale optimization algorithm (WOA) with an uncombined method to find a more optimized solution for a traveling salesman problem (TSP). The main goal is to reduce the time of solving a TSP. First, we solve the TSP with the Whale optimization algorithm, later we solve it with the combined method of solving TSP which uses the clustering method, called BIRCH (balanced iterative reducing and clustering using hierarchies). Birch builds a clustering feature (CF) tree and then applies one of the clustering methods (for ex. K-means) to cluster data. Experiments performed on three datasets show that the convergence time improves by using the combined algorithm.
Keywords
Full Text:
PDFDOI: http://doi.org/10.11591/ijai.v12.i4.pp1619-1627
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).