[N-1] Nonlinear Problems

3:45 PM - 4:00 PM JST(6:45 AM - 7:00 AM UTC)

[N-1-23] Metaheuristic Parameter Tuning Using Revised Medoid Shift Clustering

〇Rena Ohnishi¹, Nozomi Kotake¹, Takayuki Kimura¹ (1. Tokyo City University)

Keywords:

Metaheuristic,Vehicle Routing Problem,Machine Learning,K-Nearest Neighbors,Clustering

Hybrid Genetic Search (HGS) is an effective solution method for the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). A previous study proposed a K-Nearest Neighbors (KNN)-based method for predicting HGS parameters. In this study, we propose RMS-KNN, which incorporates Revised Medoid Shift (RMS) into the conventional KNN method, and evaluate its effectiveness.