A Learning—Based Particle Swarm Optimizer for Solving Mathematical Combinatorial Problems

A Learning—Based Particle Swarm Optimizer for Solving Mathematical Combinatorial Problems

This paper presents a set of adaptive parameter control methods through reinforcement learning for the particle swarm algorithm. The aim is to adjust the algorithm’s parameters during the run, to provide the metaheuristics with the ability to learn and adapt dynamically to the problem and its contex...

Full description

Bibliographic Details
Main Authors: Rodrigo Olivares, Ricardo Soto, Broderick Crawford, Víctor Ríos, Pablo Olivares, Camilo Ravelo, Sebastian Medina, Diego Nauduan
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Axioms
Subjects:
reinforcement learning
learning–based hybridizations
particle swarm optimization
mathematical combinatorial problem
Online Access:https://www.mdpi.com/2075-1680/12/7/643

Internet

https://www.mdpi.com/2075-1680/12/7/643

Similar Items