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

Year 2015, Volume 3, Issue 2, 2015, 27 - 34, 30.12.2015
https://doi.org/10.17093/aj.2015.3.2.5000148311

Abstract

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.

References

  • 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.

Seri Tedarik Zincirinde Periyodik Stok Kontrol Politikalarının Karşılaştırılması

Year 2015, Volume 3, Issue 2, 2015, 27 - 34, 30.12.2015
https://doi.org/10.17093/aj.2015.3.2.5000148311

Abstract

Tedarik zinciri yönetimi, doğru ürün veya hizmetlerin mümkün olan en iyi kalitede, doğru zamanda, doğru yerde ve uygun fiyatlı olarak müşterilere sunulmasını sağlamakta ve bu sayede müşteri tatmininin arttırılmasına yardımcı olmaktadır. Tedarik zinciri içerisinde farklı kademelerde stok bulundurulmaktadır. Tedarik zinciri sürecinde etkili ve etkin bir stok yönetimi, müşterilere sunulan hizmetleri iyileştirilmesini sağlamaktadır. Tedarik zinciri maliyetlerinin içerisinde önemli bir paya sahip olan stok maliyetlerinin azaltılması ürün veya hizmetlerin daha uygun fiyatlarla müşterilere sunulmasına yardımcı olmaktadır. Bu çalışmada seri tedarik zincirinde, (R,S) ve (R, S, Qmin) stok kontrol politikalarının karşılaştırılması amaçlanmıştır. Bu stok kontrol yöntemleri uygulandığında, toplam tedarik zinciri maliyetlerinin minimize edilmesini sağlayan “S” değerinin optimal değerini bulabilmek için simülasyon temelli genetik algoritma (GA) kullanılmış ve iki stok kontrol politikasının uygulanmasının sonuçları karşılaştırılmıştır.

References

  • 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.
There are 16 citations in total.

Details

Journal Section Articles
Authors

Nihan Kabadayı

Timur Keskintürk

Publication Date December 30, 2015
Submission Date October 23, 2015
Published in Issue Year 2015 Volume 3, Issue 2, 2015

Cite

APA Kabadayı, N., & Keskintürk, T. (2015). Comparison Of Periodic-Review Inventory Control Policies In A Serial Supply Chain. Alphanumeric Journal, 3(2), 27-34. https://doi.org/10.17093/aj.2015.3.2.5000148311

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