TY - JOUR

T1 - Dynamically adjusting the k-values of the ATCS rule in a flexible flow shop scenario with reinforcement learning

AU - Heger, Jens

AU - Voss, Thomas

N1 - Publisher Copyright: © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Titel der Ausgabe: Analytics and Machine Learning in Scheduling and Routing Optimization

PY - 2023

Y1 - 2023

N2 - Given the fact that finding the optimal sequence in a flexible flow shop is usually an NP-hard problem, priority-based sequencing rules are applied in many real-world scenarios. In this contribution, an innovative reinforcement learning approach is used as a hyper-heuristic to dynamically adjust the k-values of the ATCS sequencing rule in a complex manufacturing scenario. For different product mixes as well as different utilisation levels, the reinforcement learning approach is trained and compared to the k-values found with an extensive simulation study. This contribution presents a human comprehensible hyper-heuristic, which is able to adjust the k-values to internal and external stimuli and can reduce the mean tardiness up to 5%.

AB - Given the fact that finding the optimal sequence in a flexible flow shop is usually an NP-hard problem, priority-based sequencing rules are applied in many real-world scenarios. In this contribution, an innovative reinforcement learning approach is used as a hyper-heuristic to dynamically adjust the k-values of the ATCS sequencing rule in a complex manufacturing scenario. For different product mixes as well as different utilisation levels, the reinforcement learning approach is trained and compared to the k-values found with an extensive simulation study. This contribution presents a human comprehensible hyper-heuristic, which is able to adjust the k-values to internal and external stimuli and can reduce the mean tardiness up to 5%.

KW - Engineering

KW - Sequencing rules

KW - dynamic adjustment

KW - simulation study

KW - reinforcement learning

KW - production planning and control

UR - http://www.scopus.com/inward/record.url?scp=85109310848&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/4063b450-6da4-3b5a-918f-b6cda7cf7e07/

U2 - 10.1080/00207543.2021.1943762

DO - 10.1080/00207543.2021.1943762

M3 - Journal articles

VL - 61

SP - 147

EP - 161

JO - International Journal of Production Research

JF - International Journal of Production Research

SN - 0020-7543

IS - 1

ER -