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Estimating the Costs of Planned Changes Implied by Freezing Production Plans

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Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 236))

Abstract

The use of production planning algorithms on a rolling horizon basis is very common in practice. However, this leads to frequent changes in planned quantities for future periods which may adversely impact support activities such as material preparation, staffing, and setup planning. In this chapter we examine two widely used approaches for this problem, the use of change costs to penalize changes in planned quantities and freezing of the plan by prohibiting any changes in some number of periods in the near future. We use a linear programming model of a single-product single-stage system to develop insights into the conditions when the two approaches are equivalent. Specifically, we derive lower bounds on the values of the change costs which will ensure freezing of the plan in a given planning epoch, and present numerical results to illustrate our findings.

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References

  • Aouam T, Uzsoy R (2014) Zero-order production planning models with stochastic demand and workload-dependent lead times. Int J Prod Res 1–19. ISSN 0020-7543

    Google Scholar 

  • Bai X, Davis JS, Kanet JJ, Cantrell S, Patterson JW (2002) Schedule instability, service level and cost in a material requirements planning system. Int J Prod Res 40(7):1725–1758. ISSN 0020-7543

    Google Scholar 

  • Blackburn JD, Kropp DH, Millen RA (1985) MRP system nervousness: causes and cures. Eng Costs Prod Econ 9(1–3):141–146. ISSN 0167188X

    Google Scholar 

  • Blackburn JD, Kropp DH, Millen RA (1986) A comparison of strategies to dampen nervousness in MRP systems. Manag Sci 32(4):413–429. ISSN 0025-1909

    Google Scholar 

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

    Article  Google Scholar 

  • Braun MW, Schwartz JD (2012) A control theoretic evaluation of schedule nervousness suppression techniques for master production scheduling. In: Decision policies for production networks. Springer, London, pp 143–171

    Chapter  Google Scholar 

  • Carlson RC, Jucker JV, Kropp DH (1979) Less nervous MRP systems: a dynamic economic lot-sizing approach. Manag Sci 25(8):754–761. ISSN 0025-1909

    Google Scholar 

  • Carlson RC, Beckman SL, Kropp DH (1982) The effectiveness of extending the horizon in rolling production scheduling. Decis Sci 13(1):129–146. ISSN 0011-7315

    Google Scholar 

  • Eilon S (1975) Five approaches to aggregate production planning. IIE Trans 7(2):118–131. ISSN 0569-5554

    Google Scholar 

  • Fisher M, Ramdas K, Zheng Y (2001) Ending inventory valuation in multiperiod production scheduling. Manag Sci 47(5):679–692. ISSN 0025-1909

    Google Scholar 

  • Grinold RC (1980) Time horizons in energy planning models. In: Energy policy modeling: United States and Canadian experiences. Springer, Netherlands, pp 216–232

    Chapter  Google Scholar 

  • Grinold RC (1983) Model building techniques for the correction of end effects in multistage convex programs. Oper Res 31(3):407–431

    Article  Google Scholar 

  • Hung Y, Leachman RC (1996) A production planning methodology for semiconductor manufacturing based on iterative simulation and linear programming calculations. IEEE Trans Semicond Manuf 9(2):257–269

    Article  Google Scholar 

  • Johnson LA, Montgomery DC (1974) Operations research in production planning, scheduling, and inventory control. Wiley, New York

    Google Scholar 

  • Kadipasaoglu SN, Sridharan V (1995) Alternative approaches for reducing schedule instability in multistage manufacturing under demand uncertainty. J Oper Manag 13(3):193–221

    Article  Google Scholar 

  • Kropp DH, Carlson RC (1984) A lot-sizing algorithm for reducing nervousness in MRP systems. Manag Sci 30(2):240–244. ISSN 0025-1909

    Google Scholar 

  • Kropp DH, Carlson RC, Jucker JV (1983) Heuristic lot-sizing approached for dealing with MRP system nervousness. Decis Sci 14(2):152–169

    Article  Google Scholar 

  • Lin N, Krajewski LJ, Leong GK, Benton WC (1994) The effects of environmental factors on the design of master production scheduling systems. J Oper Manag 11(4):367–384

    Article  Google Scholar 

  • Mather H (1977) Reschedule the reschedules you just rescheduled: way of life for MRP? Prod Invent Manag 18(1):60–79

    Google Scholar 

  • Metters R, Vargas V (1999) A comparison of production scheduling policies on costs, service level, and schedule changes. Prod Oper Manag 8(1):76–91. ISSN 10591478

    Google Scholar 

  • Missbauer H, Uzsoy R (2011) Optimization models of production planning problems. In: Kempf KG, Keskinocak P, Uzsoy R (eds) Planning production and inventories in the extended enterprise: a state of the art handbook. Springer, New York, pp 437–508

    Chapter  Google Scholar 

  • Narayanan A, Robinson P (2010) Evaluation of joint replenishment lot-sizing procedures in rolling horizon planning systems. Int J Prod Econ 127(1):85–94

    Article  Google Scholar 

  • Ravindran A, Kempf KG, Uzsoy R (2011) Production planning with load-dependent lead times and safety stocks for a single product. Int J Plan Sched 1(1/2):58. ISSN 2044-494X

    Google Scholar 

  • Sahin F, Narayanan A, Robinson EP (2013) Rolling horizon planning in supply chains: review, implications and directions for future research. Int J Prod Res 51(18):5413–5430

    Article  Google Scholar 

  • Sridharan V, Berry WL (1990) Freezing the master production schedule under demand uncertainty. Decis Sci 21(1):97–120

    Article  Google Scholar 

  • Sridharan V, LaForge RL (1989) The impact of safety stock on schedule instability, cost and service. J Oper Manag 8(4):327–347. ISSN 02726963

    Google Scholar 

  • Sridharan V, LaForge RL (1994a) Freezing the master production schedule: implications for fill rate. Decis Sci 25(3):461–469

    Google Scholar 

  • Sridharan V, LaForge RL (1994b) A model to estimate service levels when a portion of the master production schedule is frozen. Comput Oper Res 21(5):477–486. ISSN 03050548

    Google Scholar 

  • Sridharan V, Berry WL, Udayabhanu V (1987) Freezing the master production schedule under rolling planning horizons. Manag Sci 33(9):1137–1149. ISSN 0025-1909

    Google Scholar 

  • Sridharan SV, Berry WL, Udayabhanu V (1988) Measuring master production schedule stability under rolling planning horizons. Decis Sci 19(1):147–166

    Article  Google Scholar 

  • Tarim SA, Kingsman BG (2004) The stochastic dynamic production/inventory lot-sizing problem with service-level constraints. Int J Prod Econ 88(1):105–119

    Article  Google Scholar 

  • Voss S, Woodruff DL (2006) Introduction to computational optimization models for production planning in a supply chain. Springer, Berlin

    Google Scholar 

  • Wagner HM, Whitin TM (1958) Dynamic version of the economic lot size model. Manag Sci 5(1):89–96. ISSN 0025-1909

    Google Scholar 

  • Xie J, Zhao X, Lee TS (2003) Freezing the master production schedule under single resource constraint and demand uncertainty. Int J Prod Econ 83(1):65–84

    Article  Google Scholar 

  • Yano CA, Carlson RC (1987) Interaction between frequency of rescheduling and the role of safety stock in material requirements planning systems. Int J Prod Res 25(2):221–232

    Article  Google Scholar 

  • Zhao X, Lam K (1997) Lot-sizing rules and freezing the master production schedule in material requirements planning systems. Int J Prod Econ 53(3):281–305

    Article  Google Scholar 

  • Zhao X, Lee TS (1993) Freezing the master production schedule for material requirements planning systems under demand uncertainty. J Oper Manag 11(2):185–205

    Article  Google Scholar 

  • Zhao X, Xie J (1998) Multilevel lot-sizing heuristics and freezing the master production schedule in material requirements planning systems. Prod Plan Control 9(4):371–384

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the National Science Foundation under Grant No.1029706. The opinions expressed in the article are those of the authors and do not represent the views of the National Science Foundation.

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Correspondence to Reha Uzsoy .

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Lin, PC., Uzsoy, R. (2016). Estimating the Costs of Planned Changes Implied by Freezing Production Plans. In: Rabadi, G. (eds) Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling. International Series in Operations Research & Management Science, vol 236. Springer, Cham. https://doi.org/10.1007/978-3-319-26024-2_2

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