---
_id: '13337'
abstract:
- lang: eng
text: In manufacturing systems with a job shop organization, queues between workstations
create an intermittent process flow, allowing workers to schedule tasks entering
the queue based on their needs and preferences. The resulting scheduling autonomy
of individual workers often leads to inefficiencies in the overall production
process due to the loss of control. Companies are therefore increasingly using
algorithmic scheduling systems to assign task sequences to workers, thereby drastically
reducing their autonomy and negatively affecting their job performance and well-being.
This paper extends the existing flexible job shop scheduling problem by sequencing
preferences (FJSPSP) to incorporate a human-centered perspective by predicting
workers’ task sequencing decisions using learning-to-rank (LTR) methods. By learning
workers’ individual task sequencing preferences, it becomes possible to predict
the processing sequence based on task characteristics. The scheduling algorithm
for the FJSPSP presented in the paper incorporates workers’ learned sequencing
preferences as constraints. Considering workers’ learned task sequencing decisions,
the FJSPSP optimizes only task assignments to maintain workers’ autonomy over
task sequences. The contributions of this paper are fourfold, namely, (1) presenting
an approach to elicit sequencing decision datasets from workers, (2) demonstrating
the successful prediction of humans’ and an actual worker’s task sequencing decisions
with LTR, (3) formulating the FJSPSP variant that integrates workers’ sequencing
preferences as constraints and proving its effectiveness in a simulation study,
and (4) consolidating these steps into an explainable artificial intelligence
(XAI)- and LTR-enabled sociotechnical system design framework. The paper closes
with a discussion of the overall methodology and future research perspectives.
article_type: original
author:
- first_name: Jan-Phillip
full_name: Herrmann, Jan-Phillip
id: '86180'
last_name: Herrmann
- first_name: Sven
full_name: Tackenberg, Sven
id: '71470'
last_name: Tackenberg
- first_name: Tharsika Pakeerathan
full_name: Srirajan, Tharsika Pakeerathan
last_name: Srirajan
- first_name: Verena
full_name: Nitsch, Verena
last_name: Nitsch
citation:
ama: 'Herrmann JP, Tackenberg S, Srirajan TP, Nitsch V. Incorporating scheduling
autonomy of workers into flexible job shop scheduling: Learning and balancing
decentralized task sequencing decisions with overall scheduling performance. Journal
of Manufacturing Systems. 2026;84(2):541-560. doi:10.1016/j.jmsy.2025.12.020'
apa: 'Herrmann, J.-P., Tackenberg, S., Srirajan, T. P., & Nitsch, V. (2026).
Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance. Journal of Manufacturing Systems, 84(2), 541–560. https://doi.org/10.1016/j.jmsy.2025.12.020'
bjps: 'Herrmann J-P et al. (2026) Incorporating Scheduling Autonomy
of Workers into Flexible Job Shop Scheduling: Learning and Balancing Decentralized
Task Sequencing Decisions with Overall Scheduling Performance. Journal of Manufacturing
Systems 84, 541–560.'
chicago: 'Herrmann, Jan-Phillip, Sven Tackenberg, Tharsika Pakeerathan Srirajan,
and Verena Nitsch. “Incorporating Scheduling Autonomy of Workers into Flexible
Job Shop Scheduling: Learning and Balancing Decentralized Task Sequencing Decisions
with Overall Scheduling Performance.” Journal of Manufacturing Systems
84, no. 2 (2026): 541–60. https://doi.org/10.1016/j.jmsy.2025.12.020.'
chicago-de: 'Herrmann, Jan-Phillip, Sven Tackenberg, Tharsika Pakeerathan Srirajan
und Verena Nitsch. 2026. Incorporating scheduling autonomy of workers into flexible
job shop scheduling: Learning and balancing decentralized task sequencing decisions
with overall scheduling performance. Journal of Manufacturing Systems 84,
Nr. 2: 541–560. doi:10.1016/j.jmsy.2025.12.020,
.'
din1505-2-1: 'Herrmann, Jan-Phillip
; Tackenberg, Sven ; Srirajan,
Tharsika Pakeerathan ; Nitsch, Verena:
Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance. In: Journal of Manufacturing Systems Bd. 84. Amsterdam, Elsevier
BV (2026), Nr. 2, S. 541–560'
havard: 'J.-P. Herrmann, S. Tackenberg, T.P. Srirajan, V. Nitsch, Incorporating
scheduling autonomy of workers into flexible job shop scheduling: Learning and
balancing decentralized task sequencing decisions with overall scheduling performance,
Journal of Manufacturing Systems. 84 (2026) 541–560.'
ieee: 'J.-P. Herrmann, S. Tackenberg, T. P. Srirajan, and V. Nitsch, “Incorporating
scheduling autonomy of workers into flexible job shop scheduling: Learning and
balancing decentralized task sequencing decisions with overall scheduling performance,”
Journal of Manufacturing Systems, vol. 84, no. 2, pp. 541–560, 2026, doi:
10.1016/j.jmsy.2025.12.020.'
mla: 'Herrmann, Jan-Phillip, et al. “Incorporating Scheduling Autonomy of Workers
into Flexible Job Shop Scheduling: Learning and Balancing Decentralized Task Sequencing
Decisions with Overall Scheduling Performance.” Journal of Manufacturing Systems,
vol. 84, no. 2, 2026, pp. 541–60, https://doi.org/10.1016/j.jmsy.2025.12.020.'
short: J.-P. Herrmann, S. Tackenberg, T.P. Srirajan, V. Nitsch, Journal of Manufacturing
Systems 84 (2026) 541–560.
ufg: 'Herrmann, Jan-Phillip u. a.: Incorporating scheduling autonomy of workers
into flexible job shop scheduling: Learning and balancing decentralized task sequencing
decisions with overall scheduling performance, in: Journal of Manufacturing
Systems 84 (2026), H. 2, S. 541–560.'
van: 'Herrmann JP, Tackenberg S, Srirajan TP, Nitsch V. Incorporating scheduling
autonomy of workers into flexible job shop scheduling: Learning and balancing
decentralized task sequencing decisions with overall scheduling performance. Journal
of Manufacturing Systems. 2026;84(2):541–60.'
date_created: 2026-01-12T08:29:09Z
date_updated: 2026-01-12T08:54:27Z
department:
- _id: DEP7027
doi: 10.1016/j.jmsy.2025.12.020
intvolume: ' 84'
issue: '2'
keyword:
- Human-centered scheduling
- Job autonomy
- Learning-to-rank
- Flexible job shop scheduling
- Human decision-making
- Explainable artificial intelligence
language:
- iso: eng
page: 541-560
place: Amsterdam
publication: Journal of Manufacturing Systems
publication_identifier:
issn:
- 0278-6125
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: 'Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance'
type: scientific_journal_article
user_id: '83781'
volume: 84
year: '2026'
...
---
_id: '11445'
abstract:
- lang: eng
text: Predicting human decisions is a central challenge for planning and controlling
production with weakly structured processes. Thus, workers’ decisions regarding
the processing strategies and the temporal sequence of tasks to be processed are
to be determined prospectively. Accordingly, there is a need to review methods
for preference elicitation to develop individual predictive decision models. This
paper presents a systematic literature review and discussion of 42 publications
on predictive decision models and decision attributes. Methods for eliciting decision-making
knowledge from manufacturing workers as part of the modeling process and decision
model validation methods are reviewed and discussed in light of their predictive
validity for individual task selection. The article synthesizes the recent literature
for predicting human decision-making in manufacturing using artificial intelligence
methods. Along with the review results, a future research agenda is proposed for
modeling and simulating human decision-making in manufacturing. Knowledge about
human preferences and the successful prediction of workers’ decision-making in
manufacturing helps companies predict manufacturing objectives and derive organizational
and work design measures.
author:
- first_name: Jan-Phillip
full_name: Herrmann, Jan-Phillip
id: '75846'
last_name: Herrmann
- first_name: Sven
full_name: Tackenberg, Sven
id: '71470'
last_name: Tackenberg
- first_name: Verena
full_name: Nitsch, Verena
last_name: Nitsch
citation:
ama: 'Herrmann JP, Tackenberg S, Nitsch V. Predicting Human Decision-Making for
Task Selection in Manufacturing: A Systematic Literature Review. IEEE Access.
2023;11:141172-141191. doi:10.1109/access.2023.3340626'
apa: 'Herrmann, J.-P., Tackenberg, S., & Nitsch, V. (2023). Predicting Human
Decision-Making for Task Selection in Manufacturing: A Systematic Literature Review.
IEEE Access, 11, 141172–141191. https://doi.org/10.1109/access.2023.3340626'
bjps: 'Herrmann J-P, Tackenberg S and Nitsch V (2023) Predicting Human Decision-Making
for Task Selection in Manufacturing: A Systematic Literature Review. IEEE Access
11, 141172–141191.'
chicago: 'Herrmann, Jan-Phillip, Sven Tackenberg, and Verena Nitsch. “Predicting
Human Decision-Making for Task Selection in Manufacturing: A Systematic Literature
Review.” IEEE Access 11 (2023): 141172–91. https://doi.org/10.1109/access.2023.3340626.'
chicago-de: 'Herrmann, Jan-Phillip, Sven Tackenberg und Verena Nitsch. 2023. Predicting
Human Decision-Making for Task Selection in Manufacturing: A Systematic Literature
Review. IEEE Access 11: 141172–141191. doi:10.1109/access.2023.3340626,
.'
din1505-2-1: 'Herrmann, Jan-Phillip
; Tackenberg, Sven ; Nitsch,
Verena: Predicting Human Decision-Making for Task Selection in Manufacturing:
A Systematic Literature Review. In: IEEE Access Bd. 11. New York, NY, IEEE
(2023), S. 141172–141191'
havard: 'J.-P. Herrmann, S. Tackenberg, V. Nitsch, Predicting Human Decision-Making
for Task Selection in Manufacturing: A Systematic Literature Review, IEEE Access.
11 (2023) 141172–141191.'
ieee: 'J.-P. Herrmann, S. Tackenberg, and V. Nitsch, “Predicting Human Decision-Making
for Task Selection in Manufacturing: A Systematic Literature Review,” IEEE
Access, vol. 11, pp. 141172–141191, 2023, doi: 10.1109/access.2023.3340626.'
mla: 'Herrmann, Jan-Phillip, et al. “Predicting Human Decision-Making for Task Selection
in Manufacturing: A Systematic Literature Review.” IEEE Access, vol. 11,
2023, pp. 141172–91, https://doi.org/10.1109/access.2023.3340626.'
short: J.-P. Herrmann, S. Tackenberg, V. Nitsch, IEEE Access 11 (2023) 141172–141191.
ufg: 'Herrmann, Jan-Phillip/Tackenberg, Sven/Nitsch, Verena: Predicting Human
Decision-Making for Task Selection in Manufacturing: A Systematic Literature Review,
in: IEEE Access 11 (2023), S. 141172–141191.'
van: 'Herrmann JP, Tackenberg S, Nitsch V. Predicting Human Decision-Making for
Task Selection in Manufacturing: A Systematic Literature Review. IEEE Access.
2023;11:141172–91.'
date_created: 2024-05-10T11:48:50Z
date_updated: 2025-06-26T07:53:23Z
department:
- _id: DEP7000
- _id: DEP7020
doi: 10.1109/access.2023.3340626
external_id:
isi:
- '001130254900001'
intvolume: ' 11'
isi: '1'
keyword:
- Artificial intelligence
- assistance system
- human decision-making
- manufacturing
language:
- iso: eng
page: 141172-141191
place: New York, NY
publication: IEEE Access
publication_identifier:
eissn:
- 2169-3536
publication_status: published
publisher: IEEE
status: public
title: 'Predicting Human Decision-Making for Task Selection in Manufacturing: A Systematic
Literature Review'
type: scientific_journal_article
user_id: '83781'
volume: 11
year: '2023'
...