Particle Swarm Optimization with Velocity Restriction and Evolutionary Parameters Selection for Scheduling Problem
Neural and Evolutionary Computing
2020-06-22 v1 Artificial Intelligence
Abstract
The article presents a study of the Particle Swarm optimization method for scheduling problem. To improve the method's performance a restriction of particles' velocity and an evolutionary meta-optimization were realized. The approach proposed uses the Genetic algorithms for selection of the parameters of Particle Swarm optimization. Experiments were carried out on test tasks of the job-shop scheduling problem. This research proves the applicability of the approach and shows the importance of tuning the behavioral parameters of the swarm intelligence methods to achieve a high performance.
Cite
@article{arxiv.2006.10935,
title = {Particle Swarm Optimization with Velocity Restriction and Evolutionary Parameters Selection for Scheduling Problem},
author = {Pavel Matrenin and Viktor Sekaev},
journal= {arXiv preprint arXiv:2006.10935},
year = {2020}
}