L-SAGA: A Learning Hyper-Heuristic Architecture for the Permutation Flow-Shop Problem

Younes Boukacem, Hatem Abdelmoumen, Hodhaifa Benouaklil, Samy Ghebache, Boualem Hamroune, Mohammed Tirichine, Nassim Ameur, Malika Bessedik, Malika Bessedik

2024

Abstract

The permutation flow-shop problem or PFSP consists in finding the optimal launching sequence of jobs to be sequentially executed along a chain of machines, each job having different execution times for each machine, in order to minimize the total completion time. As an NP-hard problem, PFSP has significant applications in large-scale industries. In this paper we present L-SAGA, a generative hyper-heuristic designed for finding optimal to sub-optimal solutions for the PFSP. L-SAGA combines a high level simulated annealing with a learning component and a low level PFSP adapted genetic algorithm. The performed tests on various benchmarks indicate that, while our method had competitive results on some small and medium size benchmarks thus showing interesting potential, it still requires further improvement to be fully competitive on larger and more complex benchmarks.

Paper Citation

in Harvard Style

Boukacem Y., Abdelmoumen H., Benouaklil H., Ghebache S., Hamroune B., Tirichine M., Ameur N. and Bessedik M. (2024). L-SAGA: A Learning Hyper-Heuristic Architecture for the Permutation Flow-Shop Problem. In Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA; ISBN 978-989-758-721-4, SciTePress, pages 321-329. DOI: 10.5220/0013020000003837

in Bibtex Style

@conference{ecta24,
author={Younes Boukacem and Hatem Abdelmoumen and Hodhaifa Benouaklil and Samy Ghebache and Boualem Hamroune and Mohammed Tirichine and Nassim Ameur and Malika Bessedik},
title={L-SAGA: A Learning Hyper-Heuristic Architecture for the Permutation Flow-Shop Problem},
booktitle={Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA},
year={2024},
pages={321-329},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013020000003837},
isbn={978-989-758-721-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA
TI - L-SAGA: A Learning Hyper-Heuristic Architecture for the Permutation Flow-Shop Problem
SN - 978-989-758-721-4
AU - Boukacem Y.
AU - Abdelmoumen H.
AU - Benouaklil H.
AU - Ghebache S.
AU - Hamroune B.
AU - Tirichine M.
AU - Ameur N.
AU - Bessedik M.
PY - 2024
SP - 321
EP - 329
DO - 10.5220/0013020000003837
PB - SciTePress