Application of dynamic pricing for variant production using reinforcement learning
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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in: CIRP Journal of Manufacturing Science and Technology, Jahrgang 60, 09.2025, S. 248-259.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Application of dynamic pricing for variant production using reinforcement learning
AU - Stamer, Florian
AU - Henzi, Matthias
AU - Lanza, Gisela
N1 - Publisher Copyright: © 2025 The Authors
PY - 2025/9
Y1 - 2025/9
N2 - In the context of variant production, the increasing volatility and customer requirements challenge the profitability of manufacturers. A promising approach to mitigate these challenges could be a dynamic pricing. An intelligent design of a continuous delivery-time-price function allows customers to choose based on their preferences and demand may be shifted to level any peaks. This way, profit, service level, and capacity usage could be improved. This work develops a dynamic pricing model based on reinforcement learning applied to a use case of the automation industry. The results show that the dynamic pricing model performs better than current methods in practice.
AB - In the context of variant production, the increasing volatility and customer requirements challenge the profitability of manufacturers. A promising approach to mitigate these challenges could be a dynamic pricing. An intelligent design of a continuous delivery-time-price function allows customers to choose based on their preferences and demand may be shifted to level any peaks. This way, profit, service level, and capacity usage could be improved. This work develops a dynamic pricing model based on reinforcement learning applied to a use case of the automation industry. The results show that the dynamic pricing model performs better than current methods in practice.
KW - Capacity levelling
KW - Dynamic pricing
KW - Reinforcement learning
KW - Variant production
KW - Volatility
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=105005958707&partnerID=8YFLogxK
U2 - 10.1016/j.cirpj.2025.05.004
DO - 10.1016/j.cirpj.2025.05.004
M3 - Journal articles
AN - SCOPUS:105005958707
VL - 60
SP - 248
EP - 259
JO - CIRP Journal of Manufacturing Science and Technology
JF - CIRP Journal of Manufacturing Science and Technology
SN - 1755-5817
ER -