Journals / Ankara Üniversitesi SBF Dergisi / 2006 / Cilt: 61 - Sayı: 4

Investigation of Cost Performance of Replenishment Cycle Policy under Non-Stationary Demand Assumption

Durağan Olmayan Talep Varsayımı Altında "Tedarik Dönemi" Politikasının Maliyet Performansı Üzerine Bir İnceleme

Pages
103–120
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Numerical tests show that Replenishment Cycle Policy (R,S) under the low ordering cost assumption has given results that are close to the min-max (s,S) policy.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the Well-known policies of inventory management min-max (s,S) and Replenishment Cycle Policy (R,S) under non-stationary demand assumption are compared in terms of cost performance.
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Key Findings & Data:The main contribution of this work is to identify the cost performance of the Replenishment Cycle Policy (R,S).
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Conclusion & Impact:Numerical tests show that Replenishment Cycle Policy (R,S) under the low ordering cost assumption has given results that are close to the min-max (s,S) policy.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, the Well-known policies of inventory management min-max (s,S) and Replenishment Cycle Policy (R,S) under non-stationary demand assumption are compared in terms of cost performance. It is known that the min-max (s,S) policy gives the optimal solution in inventory literature. The main contribution of this work is to identify the cost performance of the Replenishment Cycle Policy (R,S). The related methods of calculation for both policy parameters under the non-stationary demand assumption are investigated and compared with the cost performance over a large hypothetical experiment. Numerical tests show that Replenishment Cycle Policy (R,S) under the low ordering cost assumption has given results that are close to the min-max (s,S) policy.

Özet

Bu çalışmada envanter yönetiminin temel politikalarından olan "min-max" (s,S) ve "tedarik dönemi" (R,S) politikaları durağan olmayan talep varsayımı altında maliyet performansı bakımından karşılaştırmıştır. Envanter literatüründe "min-max" politikasının optimal çözüm verdiği gösterilmiştir. Bu çerçevede çalışmanın temel katkısı "tedarik dönemi" politikasının en iyi çözüme olan yakınlığının belirlenmesi yönündedir. Durağan olmayan talep durumu için her iki politika parametrelerinin hesaplanmasına ilişkin yöntemler incelenmiş ve maliyet performansı karşılaştırması geniş bir hipotetik deney seti üzerinde gerçekleştirilmiştir. Test sonuçlan "tedarik dönemi" yaklaşımının özellikle düşük sipariş maliyeti altında "min-max" politikasına çok yakın sonuçlar verdiğini göstermiştir.

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Cite This Article

TAŞ, A., CAN, M. (2022). Investigation of Cost Performance of Replenishment Cycle Policy under Non-Stationary Demand Assumption. Ankara Üniversitesi SBF Dergisi, Cilt: 61 - Sayı: 4, 103–120. https://ajindex.com/articles/443238

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References (14)

  1. BLACKBURN, D. Joseph/ KROPP, H. Dean / MILLEN Robert (1986), "A Comparison of Strategies to Dampen Nervousness in MRP Systems," Management Science, 32: 413-429.
  2. BERRY, William (1972), "Lot Sizing Procedures for Requirements Planning Systems: A Framework for Analysis," Production and Inventory Management, 2:19-34.
  3. BOLLAPRAGADA, Srinivas/ MORTON, Thomas (1999), "A Simple Heuristic for Computing Nonstationary (s,S) Policies," Operations Research, 47: 576-584.
  4. BOOKBINDER, James / TAN, Jin-Yan (1988), "Strategies for the Probabilistic Lot-sizing Pproblem with Service-level Constraints," Management Science, 34:1096-1108.
  5. CHIKAN, Attila (1990), Inventory Models (London: Springer). DE KOK, Ton / INDERFURTH, Karl (1997), "Nervousness in Inventory Management: Comparison of Bbasic Control Rules," European Journal of Operational Research, 103: 55-82.
  6. EHRHARDT, Richard (1979) "The Power Approximation for Computing (s, S) Inventory Policies," ' Management Science, XXV, 8:777-786.
  7. HARRIS, F.W. (1915), "Operation and Cost," Factory Management Series, 48-52.
  8. HEISIG, Gerald (2001), "Comparison of (s,S) and (s,nQ) Inventory Control Rules with Respect to Planning Stability," International Journal of Production Economics, 73:59-82.
  9. INDEFURTH, Karl (1994), "Nervousness in Inventory Control," OR Spectrum, 16:113-123.
  10. NADDOR, Eliezer (1966), Inventory Systems (New York: John Wiley & Sons). SCARF, Herbert (1960), "The Optimality of (s,S) Policies in the Dynamic Inventory Problem," ARROW, K.J. / KARUN, S. /SUPPES, P. (eds.), Mathematical Methods in the Social Sciences 1959 (Stanford: Stanford University Press: 196-202.
  11. SILVER, A. Edward / MEAL, H.C. (1973), "A Heuristic for Selecting Lot Size Requirements for the Case of a Deterministic Time-Varying Demand Rate and Discrete Opportunities for Replenishment," Production and Inventory Management, XIV, 2:64:74. SILVER, Edward (1978), "Inventory Control Under a Probabilistic Time Varying, Demand Pattern," AIIE Transactions, 371-379.
  12. SIPPER, Daniel / BULFIN, Robert L.(1997),
  13. Production Planning, Control and Integration (USA: McGraw-Hill). TAHA, A. Hamdy (1987) Operations Research an Introduction (New York: Mac Millen Publishing Company, Fourth Edition). TARIM, S. Armağan / KINGSMAN, G. Brian (2004), "The Sstochastic Dynamic Production/Inventory Lot-sizing Problem with Services-level Constraints," International Journal of Production Economics, 88:105-119.
  14. TARIM, S. Armağan / KINGSMAN, G. Brian (2005), "Modeling and Computing (RntSn) Polic