Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain

1.645 636


Supply chain management provides customers with the right product or service at a reasonable price, in the right place, at the right time, and with the best quality possible, thus increasing customer satisfaction. The inventory is held at the multiple sites in a supply chain. Effective and efficient management of inventory in the supply chain process has a significant impact on improving the ultimate customer service provided to the customer. Reducing inventory cost, which is a major part of total supply chain costs, will help provide products or services at a better price. This study aims to compare (R, S) and (R, S, Qmin) inventory control policies in a serial supply chain.  We develop a simulation based genetic algorithm (GA) in order to find the optimal numerical "S" value that minimizes the total supply chain cost (TSCC) and compare our results between two methods.

Full Text:




Axsäter, S. (2007). Inventory control (Vol. 90). Springer Science & Business Media.

Axsäter, S., & Rosling, K. (1993). Notes: Installation vs. echelon stock policies for multilevel inventory control. Management Science, 39(10), 1274-1280.

Azadivar, F., & Tompkins, G. (1999). Simulation optimization with qualitative variables and structural model changes: A genetic algorithm approach. European Journal of Operational Research, 113(1), 169-182.

Chambers, J. (1995). Practical Handbook of Genetic Algorithms: Volume 2: New Frontiers, CRC-Press; 1 edition.

Chen, F. (1999). On (R, NQ) policies in serial inventory systems. In Quantitative models for supply chain management (pp. 71-109). Springer US.

Chopra S. & Meindl P. (2010). Supply Chain Management: Strategy, Planning and Operation, Prentice-Hall Inc., New Jersey.

Ding, H., Benyoucef, L., & Xie, X. (2006). A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization. Engineering Applications of Artificial Intelligence, 19(6), 609-623.

Kapuscinski, R., & Tayur, S. (1999). Optimal policies and simulation-based optimization for capacitated production inventory systems. In Quantitative Models for Supply Chain Management (pp. 7-40). Springer US.

Kiesmüller, G. P., De Kok, A. G., & Dabia, S. (2011). Single item inventory control under periodic review and a minimum order quantity. International Journal of Production Economics, 133(1), 280-285.

Lee, H. L., & Billington, C. (1992). Managing supply chain inventory: pitfalls and opportunities. Sloan management review, 33(3).

Marseguerra, M., Zio, E., & Podofillini, L. (2002). Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation. Reliability Engineering & System Safety, 77(2), 151-165.

Nahmias S. (2009). Production and Operation Analysis, McGraw-Hill International edition, New York.

Petrovic, D., Roy, R., & Petrovic, R. (1998). Modelling and simulation of a supply chain in an uncertain environment. European journal of operational research, 109(2), 299-309.

Simchi-Levi D., Kaminsky P., Simchi-Levi E. (2000). Designing and Managing the Supply Chain, Irwin McGraw-Hill.

Talbi El-G. (2009). Metaheuristics, John Wiley & Sons, Inc.

Zhou, B., Zhao, Y., & Katehakis, M. N. (2007). Effective control policies for stochastic inventory systems with a minimum order quantity and linear costs. International Journal of Production Economics, 106(2), 523-531.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.