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Approaches for periodic inventory control under random production yield and fixed setup cost

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A Publisher Correction to this article was published on 24 January 2018

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Abstract

In this paper, we study a multi-period inventory control problem with random demand and stochastically proportional production yield. The model includes nonzero processing lead time as well as fixed setup cost for a replenishment order. From prior research, it is evident that the optimal control rule must have a highly complex structure so that only simple policies are reasonable candidates for practical problem solving. In this paper, we propose a periodic review (sS) policy with simple order inflation and compare different heuristic approaches for determining the two policy parameters. Two of these approaches are taken from the literature and, partly, adjusted to fit into the periodic-review planning context. A comprehensive numerical study reveals that both methods perform insufficiently, mainly because they do not take into account the yield risk from open orders during lead time. Therefore, three new approaches for parameter determination are developed, which consider this risk but follow very different concepts in their design. Two of these approaches follow simple-to-implement ideas for parameter adjustment to demand and yield risks and can be applied as spreadsheet applications, while the third one is based on an approximation of the objective value as function of the parameters s and S,  which then must be computed numerically. From the experimental study, it turns out that all three approaches have a similarly high performance, not only concerning their average but also their worst-case behavior. The numerical study also provides insights into how yield randomness affects the policy parameters and elements of total expected cost.

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Change history

  • 24 January 2018

    In the original version of the article, operator symbols “⌊   ⌋” “⌈   ⌉” have been inadvertently processed as square brackets in equations 17, 20, the first line of the third paragraph and second line of the fourteenth paragraph in Sect. 4.1.

References

  • Babai MZ, Syntetos AA, Teunter R (2010) On the empirical performance of (T, s, S) heuristics. Eur J Oper Res 202:466–472

    Article  Google Scholar 

  • Bitran GR, Gilbert SM (1994) Co-production processes with random yields in the seminconductor industry. Oper Res 42(3):476–491

    Article  Google Scholar 

  • Bollapragada S, Morton TE (1999) Myopic heuristics for the random yield problem. Oper Res 47(5):713–722

    Article  Google Scholar 

  • Bookbinder JH, Tan JY (1988) Strategies for probabilistic lot-sizing problems with service-level constraints. Manag Sci 34(9):1096–1108

    Article  Google Scholar 

  • Denardo EV (1982) Dynamic programming: models and applications. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Dettenbach M, Thonemann UW (2015) The value of real time yield information in multi-stage inventory systems—exact and heuristic approaches. Eur J Oper Res 240:72–83

    Article  Google Scholar 

  • Ehrhardt R, Taube L (1987) An inventory model with random replenishment quantities. Int J Prod Res 25(12):1795–1803

    Google Scholar 

  • Gerchak Y, Vickson RG, Parlar M (1988) Periodic review production models with variable yield and uncertain demand. IIE Trans 20(2):144–150

    Article  Google Scholar 

  • Grasman SE, Sari Z, Sari T (2007) Newsvendor solutions with general random yield distributions. RAIRO-Oper Res 41(4):455–64

    Article  Google Scholar 

  • Grosfeld-Nir A, Gerchak Y (2004) Multiple lotsizing in production to order with random yields: review of recent advances. Ann Oper Res 126:43–69

    Article  Google Scholar 

  • Gurnani H, Akella R, Lehoczky J (2000) Supply management in assembly systems with random yield and random demand. IIE Trans 32(8):701–714

    Google Scholar 

  • Hadley G, Whitin TM (1963) Analysis of inventory systems. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Henig M, Gerchak Y (1990) The structure of periodic review policies in the presence of random yield. Oper Res 38(4):634–643

    Article  Google Scholar 

  • Huh WT, Nagarajan M (2010) Linear inflation rules for the random yield problem: analysis and computations. Oper Res 58(1):244–251

    Article  Google Scholar 

  • Iglehart DL (1963) Optimality of \((s, S)\) policies in the infinite horizon dynamic inventory problem. Manage Sci 9(2):259–267

    Article  Google Scholar 

  • Inderfurth K, Kiesmüller GP (2015) Exact and heuristic linear inflation policies for an inventory model with random yield and arbitrary lead times. Eur J Oper Res 245(1):109–120

    Article  Google Scholar 

  • Inderfurth K, Vogelgesang S (2013) Concepts for safety stock determination under stochastic demand and different types of random yield. Eur J Oper Res 224:293–301

    Article  Google Scholar 

  • Jones PC, Lowe TJ, Traub RD, Kegler G (2001) Matching supply and demand: the value of a second chance in producing hybrid seed corn. Manuf Serv Oper Manag 3(2):122–137

    Article  Google Scholar 

  • Kazaz B (2004) Production planning under yield and demand uncertainty with yield-dependent cost and price. Manuf Serv Oper Manag 6(3):209–224

    Article  Google Scholar 

  • Mazzola JB, McCloy WF, Wagner HM (1987) Algorithms and heuristics for variable-yield lot sizing. Naval Res Logist 34:67–86

    Article  Google Scholar 

  • Moinzandeh K, Lee HL (1987) A continuous-review inventory model with constant resupply time and defective items. Naval Res Logist 34:457–467

    Article  Google Scholar 

  • Nahmias S (2009) Production and operations analysis, 6th edn. McGraw-Hill, Boston

    Google Scholar 

  • Lin LC, Hou KL (2005) An inventory system with investment to reduce yield variability and set-up cost. J Oper Res Soc 56:67–74

    Article  Google Scholar 

  • Noori AH, Keller G (1986) The lot-size reorder-point model with upstream-downstream uncertainty. Decis Sci 17:285–291

    Article  Google Scholar 

  • Özekici S, Parlar M (1999) Inventory models with unreliable suppliers in a random environment. Ann Oper Res 91:123–136

    Article  Google Scholar 

  • Paknejad MJ, Nasri F, Affisco JF (1995) Defective units in a continuous review \((s, Q)\) system. Int J Prod Res 33(10):2767–2777

    Article  Google Scholar 

  • Parlar M, Wang Y, Gerchak Y (1995) A periodic review inventory model with Markovian supply availability. Int J Prod Econ 42:131–136

    Article  Google Scholar 

  • Porteus EL (1985) Numerical comparisons of inventory policies for periodic review systems. Oper Res 33(1):134–152

    Article  Google Scholar 

  • Rajaram K, Kamarkar US (2002) Product cycling with uncertain yields: analysis and application to the process industry. Oper Res 50(4):680–691

    Article  Google Scholar 

  • Scarf H (1960) The optimality of \((s, S)\) policies in dynamic inventory problem. In: Arrow K, Karlin S, Suppes P (eds) Mathematical methods in the social sciences. Stanford University Press, Stanford

    Google Scholar 

  • Schneider H, Rinks DP (1989) Optimal policy surfaces for a multi-item inventory problem. Eur J Oper Res 39:180–191

    Article  Google Scholar 

  • Silver EA (1976) Establishing the reorder quantity when the amount received is uncertain. INFOR 14(1):32–39

    Google Scholar 

  • Song Y, Wang Y (2017) Periodic review inventory systems with fixed order cost and uniform random yield. Eur J Oper Res 257(1):106–117

    Article  Google Scholar 

  • Tempelmeier H (2006) Inventory management in supply networks: problems, models, solutions. Books on Demand

  • Tempelmeier H (2013) Stochastic lot sizing problems. In: MacGregor Smith J, Tan B (eds) Handbook of stochastic models and analysis of manufacturing operations. Springer, New York, pp 313–344

    Chapter  Google Scholar 

  • Tijms HC (1994) Stochastic models: an algorithmic approach. Wiley, Chichester

    Google Scholar 

  • Wang D, Tang O, Zhang L (2014) A periodic review lot sizing problem with random yields, disruptions and inventory capacity. Int J Prod Econ 155:330–339

    Article  Google Scholar 

  • Yano CA, Lee HL (1995) Lot sizing with random yields: a review. Oper Res 43(2):311–334

    Article  Google Scholar 

  • Zipkin PH (2000) Foundations of inventory management. McGraw-Hill, New York

    Google Scholar 

Download references

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Correspondence to G. P. Kiesmüller.

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The original version of this article was revised: operator symbols “\({\lfloor \rfloor }\)”“\({\lceil \rceil }\)” have been inadvertently processed as square brackets in equations 17, 20, the first line of the third paragraph and second line of the fourteenth paragraph in section 4.1. The equations and text have been corrected in this article.

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Kiesmüller, G.P., Inderfurth, K. Approaches for periodic inventory control under random production yield and fixed setup cost. OR Spectrum 40, 449–477 (2018). https://doi.org/10.1007/s00291-017-0489-8

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