Artificial Bee Colony Algorithm: Bottom-Up Variants for the Job-Shop Scheduling Problem

K. Youssefi, M. Gojkovic, M. Schranz

2024

Abstract

The optimization of a job-shop scheduling problem, e.g., in the semiconductor industry, is an NP-hard problem. Various research work have shown us that agent-based modeling of such a production plant allows to efficiently plan tasks, maximize productivity (utilization and tardiness) and thus, minimize production delays. The optimization from the bottom-up especially overcomes computational barriers associated with traditional, typically centrally calculated optimization methods. Specifically, we consider a dynamic semiconductor production plant where we model machines and products as agents and propose two variants of the artificial bee colony algorithm for scheduling from the bottom-up. Variant (1) prioritizes decentralization and batch processing to boost production speed, while Variant (2) aims to predict production times to minimize queue delays. Both algorithmic variants are evaluated in the framework SwarmFabSim, designed in NetLogo, focusing on the job-shop scheduling problem in the semiconductor industry. With the evaluation we analyze the effectiveness of the bottom-up algorithms, which rely on low-effort local calculations.

Paper Citation

in Harvard Style

Youssefi K., Gojkovic M. and Schranz M. (2024). Artificial Bee Colony Algorithm: Bottom-Up Variants for the Job-Shop Scheduling Problem. In Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH; ISBN 978-989-758-708-5, SciTePress, pages 103-111. DOI: 10.5220/0012765900003758

in Bibtex Style

@conference{simultech24,
author={K. Youssefi and M. Gojkovic and M. Schranz},
title={Artificial Bee Colony Algorithm: Bottom-Up Variants for the Job-Shop Scheduling Problem},
booktitle={Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH},
year={2024},
pages={103-111},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012765900003758},
isbn={978-989-758-708-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH
TI - Artificial Bee Colony Algorithm: Bottom-Up Variants for the Job-Shop Scheduling Problem
SN - 978-989-758-708-5
AU - Youssefi K.
AU - Gojkovic M.
AU - Schranz M.
PY - 2024
SP - 103
EP - 111
DO - 10.5220/0012765900003758
PB - SciTePress