Parameter Prediction for Metaheuristic Algorithms Solving Routing Problem Instances Using Machine Learning
Date Issued
2025-03
Author(s) USM
DOI
10.3390/app15062946
Abstract
Setting parameter values is crucial for the performance of metaheuristics. Tuning the parameters of a metaheuristic is a computationally costly task. Moreover, parameter tuning is difficult considering their inherent stochasticity and problem instance dep
