Simulation based optimization of lot sizes for opposing logistic objectives
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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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
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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 -