Abstract
Inventory management is one of the most important factors in logistics operations. However, real-world inventory systems are complexly intertwined with related elements, and determining the optimal parameters and identifying the determining factors that influence inventory changes are complex problems. In this paper, using real POS data, we propose a simulation-based algorithm to optimize automated refreshment systems in a retail environment. The inventory system is modeled and simulated, which then returns the performance functions. The expectations of these functions are then estimated by an algorithm and the optimal combination result is obtained. Based on the sensitivity analysis, the determining factor that influences inventory changes is identified. The results show that the proposed simulation-based algorithm is powerful and effective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
ARIMA models applied to distribution operations. IT Solut. Front. 10, 6–9 (2011)
A. Arisha, W.A. Hamad, Simulation optimization methods in supply chain applications. Ir. J. Manag. 90–124 (2010)
A.M. Law, M.G. McComas, Simulation optimization: simulation-based optimization, in Proceedings of the 2002 Winter Simulation Conference, ed. by E. Yucesan, C.H. Chen, J.L. Snowdon, J.M. Charnes (Institute of Electrical and Electronics Engineers, Inc, Piscataway, NJ, 2002), pp. 41–44
J.R. Swisher, D.H. Paul, H.J. Sheldon, W.S. Lee, A survey of simulation optimization techniques and procedures, in Proceedings of the 2000 Winter Simulation Conference, ed. by J.A. Joines, R.R. Barton, K. Kang, P.A. Fishwick (Institute of Electrical and Electronics Engineers, Inc, Piscataway, NJ, 2000), pp. 119–128
X. Wan, J.F. Pekny, G.V. Reklaitis, Simulation-based optimization with surrogate models—application to supply chain management. Comput. Chem. Eng. 29(6), 1317–1328 (2005)
Y. Chu, F. You, Simulation-based optimization for multi-echelon inventory systems under uncertainty, in Proceedings of the 2014 Winter Simulation Conference, ed. by A. Tolk, S.Y. Diallo, I.O. Ryzhov, L. Yilmaz, S. Buckley, J.A. Miller (Institute of Electrical and Electronics Engineers, Inc, Piscataway, NJ, 2014), pp. 385–394
X. Zheng, M. He, L. Tang, C. Ren, B. Shao, A multiple-purpose simulation-based inventory optimization system: applied to a large detergent company in China, in Proceedings of the 2015 Winter Simulation Conference, ed. by L. Ylimaz, W.K.V. Chan, I. Moon, T.M.K. Roeder, C. Macal, M.D. Rossetti (Institute of Electrical and Electronics Engineers, Inc, Piscataway, NJ, 2015), pp. 1218–1229
H. Sang, S. Takakuwa, A simulation-based approach for obtaining optimal order quantities of short-expiration date items at a retail store, in Proceedings of the 2012 Winter Simulation Conference, ed. by C. Laroque, J. Himmelspach. R, Pasupathy, O. Rose, A.M. Uhrmacher (Institute of Electrical and Electronics Engineers, Inc, Piscataway, NJ, 2012), pp. 1466–1477
D.J. Yue, F.Q. You, Planning and scheduling of flexible process networks under uncertainty with stochastic inventory: MINLP models and algorithm. AIChE J. 59, 1511–1532 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sang, H., Takahashi, S., Gaku, R. (2019). Big Data-Driven Simulation Analysis for Inventory Management in a Dynamic Retail Environment. In: Huang, G., Chien, CF., Dou, R. (eds) Proceeding of the 24th International Conference on Industrial Engineering and Engineering Management 2018. Springer, Singapore. https://doi.org/10.1007/978-981-13-3402-3_72
Download citation
DOI: https://doi.org/10.1007/978-981-13-3402-3_72
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-3401-6
Online ISBN: 978-981-13-3402-3
eBook Packages: Business and ManagementBusiness and Management (R0)