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Simulation based optimization of lot sizes for opposing logistic objectives

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

Simulation based optimization of lot sizes for opposing logistic objectives. / Maier, Janine Tatjana; Voß, Thomas; Heger, Jens et al.
Advances in Production Management Systems : Towards Smart Production Management Systems; IFIP WG 5.7 International Conference, APMS 2019 Austin, TX, USA, September 1–5, 2019; Proceedings, Part II. ed. / Farhad Ameri; Kathryn E. Stecke; Gregor von Cieminski; Dimitris Kiritsis. Vol. 2 Cham: Springer Verlag, 2019. p. 171-179 (IFIP Advances in Information and Communication Technology; Vol. 567).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Maier, JT, Voß, T, Heger, J & Schmidt, M 2019, Simulation based optimization of lot sizes for opposing logistic objectives. in F Ameri, KE Stecke, G von Cieminski & D Kiritsis (eds), Advances in Production Management Systems : Towards Smart Production Management Systems; IFIP WG 5.7 International Conference, APMS 2019 Austin, TX, USA, September 1–5, 2019; Proceedings, Part II. vol. 2, IFIP Advances in Information and Communication Technology, vol. 567, Springer Verlag, Cham, pp. 171-179. https://doi.org/10.1007/978-3-030-29996-5_20

APA

Maier, J. T., Voß, T., Heger, J., & Schmidt, M. (2019). Simulation based optimization of lot sizes for opposing logistic objectives. In F. Ameri, K. E. Stecke, G. von Cieminski, & D. Kiritsis (Eds.), Advances in Production Management Systems : Towards Smart Production Management Systems; IFIP WG 5.7 International Conference, APMS 2019 Austin, TX, USA, September 1–5, 2019; Proceedings, Part II (Vol. 2, pp. 171-179). (IFIP Advances in Information and Communication Technology; Vol. 567). Springer Verlag. https://doi.org/10.1007/978-3-030-29996-5_20

Vancouver

Maier JT, Voß T, Heger J, Schmidt M. Simulation based optimization of lot sizes for opposing logistic objectives. In Ameri F, Stecke KE, von Cieminski G, Kiritsis D, editors, Advances in Production Management Systems : Towards Smart Production Management Systems; IFIP WG 5.7 International Conference, APMS 2019 Austin, TX, USA, September 1–5, 2019; Proceedings, Part II. Vol. 2. Cham: Springer Verlag. 2019. p. 171-179. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-030-29996-5_20

Bibtex

@inbook{ac6035fb89164b0e9297930a230da5b3,
title = "Simulation based optimization of lot sizes for opposing logistic objectives",
abstract = "The objective of this study is to optimize the lot sizes for three different products based on storage cost, set up cost and logistic key performance indicators (KPIs) such as delivery reliability. Two methods including a mathematical model and the static method of Andler{\textquoteright}s lot size were originally used to solve this problem. However, both methods produce lot sizes that underperform according to logistic KPIs. For that reason, a simulation considering dynamic behavior and logistic performance is developed to heuristically optimize the lot sizes while being restricted to a minimum standard of delivery reliability. The study indicates that modifying the lot sizes will improve the logistic performance without increasing the total costs drastically. Compared to Andler{\textquoteright}s static method, the heuristically-optimized lot sizes show an average increase of the delivery reliability by 7% and a reduction of the total cost by 13%. Throughput time was raised by more than 25% and the utilization elevated by 4%. ",
keywords = "Engineering, Lot sizing, Simulation, logistic objectives",
author = "Maier, {Janine Tatjana} and Thomas Vo{\ss} and Jens Heger and Matthias Schmidt",
year = "2019",
month = sep,
day = "1",
doi = "10.1007/978-3-030-29996-5_20",
language = "English",
isbn = "978-3-030-29995-8",
volume = "2",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer Verlag",
pages = "171--179",
editor = "Farhad Ameri and Stecke, {Kathryn E.} and {von Cieminski}, Gregor and Dimitris Kiritsis",
booktitle = "Advances in Production Management Systems",
address = "Germany",

}

RIS

TY - CHAP

T1 - Simulation based optimization of lot sizes for opposing logistic objectives

AU - Maier, Janine Tatjana

AU - Voß, Thomas

AU - Heger, Jens

AU - Schmidt, Matthias

PY - 2019/9/1

Y1 - 2019/9/1

N2 - The objective of this study is to optimize the lot sizes for three different products based on storage cost, set up cost and logistic key performance indicators (KPIs) such as delivery reliability. Two methods including a mathematical model and the static method of Andler’s lot size were originally used to solve this problem. However, both methods produce lot sizes that underperform according to logistic KPIs. For that reason, a simulation considering dynamic behavior and logistic performance is developed to heuristically optimize the lot sizes while being restricted to a minimum standard of delivery reliability. The study indicates that modifying the lot sizes will improve the logistic performance without increasing the total costs drastically. Compared to Andler’s static method, the heuristically-optimized lot sizes show an average increase of the delivery reliability by 7% and a reduction of the total cost by 13%. Throughput time was raised by more than 25% and the utilization elevated by 4%.

AB - The objective of this study is to optimize the lot sizes for three different products based on storage cost, set up cost and logistic key performance indicators (KPIs) such as delivery reliability. Two methods including a mathematical model and the static method of Andler’s lot size were originally used to solve this problem. However, both methods produce lot sizes that underperform according to logistic KPIs. For that reason, a simulation considering dynamic behavior and logistic performance is developed to heuristically optimize the lot sizes while being restricted to a minimum standard of delivery reliability. The study indicates that modifying the lot sizes will improve the logistic performance without increasing the total costs drastically. Compared to Andler’s static method, the heuristically-optimized lot sizes show an average increase of the delivery reliability by 7% and a reduction of the total cost by 13%. Throughput time was raised by more than 25% and the utilization elevated by 4%.

KW - Engineering

KW - Lot sizing

KW - Simulation

KW - logistic objectives

UR - http://www.scopus.com/inward/record.url?scp=85072957020&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-29996-5_20

DO - 10.1007/978-3-030-29996-5_20

M3 - Article in conference proceedings

SN - 978-3-030-29995-8

VL - 2

T3 - IFIP Advances in Information and Communication Technology

SP - 171

EP - 179

BT - Advances in Production Management Systems

A2 - Ameri, Farhad

A2 - Stecke, Kathryn E.

A2 - von Cieminski, Gregor

A2 - Kiritsis, Dimitris

PB - Springer Verlag

CY - Cham

ER -

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Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Einsatz von bestärkendem Lernen in der Reihenfolgeplanung mit dem Ziel der platzeffizienten Produktion

Müller, K. & Heger, J., 2025, Simulation in Produktion und Logistik. Dresden: ASIM - Arbeitsgemeinschaft Simulation, Vol. 21.

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Enhancing SME Production Efficiency: A Case Study on Autonomous Manufacturing Systems

Prüfer, O. C. & Heger, J., 2025, In: Procedia CIRP. 134, p. 313-318 6 p.

Research output: Journal contributions › Conference article in journal › Research › peer-review

Implementierung von Produktrückführungsprozessen in bestehende Produktionsabläufe: Herausforderungen und Anforderungen

Sandner, S., Nübel, M., Schulz, J., Metternich, J. & Schmidt, M., 20.06.2025, In: ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb. 120, 6, p. 397-403 7 p.

Research output: Journal contributions › Journal articles › Research › peer-review

Machine Learning For Determining Planned Order Lead Times In Job Shop Production: A Systematic Review Of Input Factors And Applied Methods

Wolter, F., Rokoss, A. & Schmidt, M., 2025, Conference on Production Systems and Logistics: University of San Ignacio de Loyola Lima, Peru, 18th – 21th March 2025, Proceedings. Herberger, D. & Hübner, M. (eds.). Offenburg: publish-Ing., p. 374-384 11 p. 32. (Proceedings of the ... Conference on Production Systems and Logistics; no. 7).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

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