Skip to main content
SpringerLink
Log in

Optimization Models of Production Planning Problems

  • Chapter
  • First Online:
Planning Production and Inventories in the Extended Enterprise

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 151))

Abstract

Production planning problems have been formulated and solved as optimization problems since the early 1950s, and an extensive literature has been developed. The widespread use of Enterprise Resource Planning systems and developments in information technology and scientific computing have opened the way for even wider use of these techniques in industry. In this chapter, we review the basic formulations that have been the mainstay of academic research and industrial practice for the last five decades, assess their strengths and weaknesses, and discuss a number of interesting new directions that have emerged recently. We especially focus on models that support decisions on production volumes and order release over time and highlight the related issues on determining planned lead times.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Simulation results indicate that traditional order release mechanisms can in fact reduce average total throughput time of orders (pool waiting time plus shop flow time) and do not just shift the waiting time from the shop to the pool, possibly increasing total flow time due to reduced shop capacity (for this critique, see Kanet 1988). A possible reason is the load balancing effect. A good order release mechanism limits the shop load, but it also aims at keeping the level of WIP at the target level for each work center, thus balancing the load among the work centers by releasing orders with different routing. (For simulation results on total throughput time reduction, see Land 2004.)

  2. 2.

    In general, we use the term flow time when we consider this time span from a manufacturing perspective, and the term lead time when it is considered from a planning perspective; see Hopp and Spearman (2001, p. 321). The terms are not always clearly distinguished in the literature.

  3. 3.

    This assumes a production unit consisting of a single work center, which we assume for exposition. For a multistage system as in Sect.16.5.2, the work release R it is replaced by the work input from release and from the other work centers as in (16.47).

  4. 4.

    Due to the computational complexity, the summation in (16.61) has been performed for n=0,…, 80 in the numerical examples below. This ignores at most 1.5% of the cases (for ρ=0.95 in steady state), in most cases the error is close to zero.

  5. 5.

    The index for the periods (discrete time) is denoted as subscript, the continuous time is denoted in parenthesis.

  6. 6.

    We are aware of the similar GI∕G∕1 approximation by Krämer and Langenbach-Belz (1976) that distinguishes between \({c}_{a}^{2} \leq1\) and \({c}_{a}^{2} > 1\) (Tijms 1994), where c a and c s are not additive.

References

  • Agnew C (1976) Dynamic modeling and control of some congestion prone systems. Oper Res 24(3):400–419

    Google Scholar 

  • Andersson H, Axsater S et al. (1981) Hierarchical material requirements planning. Int J Prod Res 19(1):45–57

    Google Scholar 

  • Anli OM, Caramanis M et al. (2007). Tractable supply chain production planning modeling non-linear lead time and quality of service constraints. J Manuf Syst 26(2):116–134

    Google Scholar 

  • Anthony RN (1966) Planning and control systems: a framework for analysis. Harvard University Press, Cambridge

    Google Scholar 

  • Asmundsson JM, Rardin RL et al. (2006) Tractable nonlinear production planning models for semiconductor wafer fabrication facilities. IEEE Trans Semicond Manuf 19:95–111

    Google Scholar 

  • Asmundsson JM, Rardin RL et al. (2009) Production planning models with resources subject to congestion. Naval Res Log 56:142–157

    Google Scholar 

  • Baker KR (1993) Requirements planning. In: Graves SC, Rinnooy Kan AHG, Zipkin PH. Logistics of production and inventory. Handbooks in operations research and management science, vol 3. Elsevier Science, Amsterdam, pp 571–627

    Google Scholar 

  • Bergamaschi D, Cigolini R et al. (1997) Order review and release strategies in a job shop environment: a review and a classification. Int J Prod Res 35:399–420

    Google Scholar 

  • Bermon S, Hood SJ (1999) Capacity optimization planning system (CAPS). Interfaces 29(5):31–50

    Google Scholar 

  • Bertrand JWM, Wortmann JC (1981) Production control and information systems for component-manufacturing shops. Elsevier, Amsterdam

    Google Scholar 

  • Bertrand JWM, Wortmann JC et al. (1990) Production control: a structural and design oriented approach. Elsevier, Amsterdam

    Google Scholar 

  • Bertsimas D, Gamarnik D et al. (2003) From fluid relaxations to practical algorithms for high-multiplicity job shop scheduling: the holding cost objective. Oper Res 51(5):798–813

    Google Scholar 

  • Bertsimas D, Sethuraman J (2002) From fluid relaxations to practical algorithms for job shop scheduling: the makespan objective. Math Program Series A 92:61–102

    Google Scholar 

  • Birge JR, Louveaux F (1997) Introduction to stochastic programming. Springer, New York

    Google Scholar 

  • Bitran GR, Haas EA et al. (1981) Hierarchical production planning: a single stage system. Oper Res 29(4):717–743

    Google Scholar 

  • Bitran GR, Haas EA et al. (1982) Hierarchical production planning: a two-stage system. Oper Res 30(2):232–251

    Google Scholar 

  • Bitran GR, Tirupati D (1993) Hierarchical production planning. Graves SC, Rinnooy Kan AHG, Zipkin PH Logistics of production and inventory. Handbooks in operations research and management science, vol. 4. Elsevier Science, Amsterdam, pp 523–568

    Google Scholar 

  • Blau RA (1974) Stochastic programming and decision analysis: an apparent dilemma. Manage Sci 21(3):271–276

    Google Scholar 

  • Bookbinder JH, H’ng BT (1986) Rolling horizon production planning for probabilistic time-varying demands. Int J Prod Res 24(6):1439–1458

    Google Scholar 

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

    Google Scholar 

  • Bowman EB (1956) Production scheduling by the transportation method of linear programming. Oper Res 4(1):100–103

    Google Scholar 

  • Buzacott JA, Shanthikumar JG (1993) Stochastic models of manufacturing systems. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Byrne MD, Bakir MA (1999) Production planning using a hybrid simulation-analytical approach. Int J Prod Econ 59:305–311

    Google Scholar 

  • Byrne MD, Hossain MM (2005) Production planning: an improved hybrid approach. Int J Prod Econ 93–94:225–229

    Google Scholar 

  • Caramanis M, Pan H et al. (2001) A closed-loop approach to efficient and stable supply chain coordination in complex stochastic manufacturing. American Control Conference, Arlington, VA, 1381–1388

    Google Scholar 

  • Carey M (1987) Optimal time-varying flows on congested networks. Oper Res 35(1):58–69

    Google Scholar 

  • Carey M, Subrahmanian E (2000) An approach to modelling time-varying flows on congested networks. Transp Res B 34:157–183

    Google Scholar 

  • Cassidy M (2003) Traffic flow and capacity. In: Hall RW (ed) Handbook of transportation science. Kluwer Academic, Dordrecht, pp 155–191

    Google Scholar 

  • Charnes A, Cooper WW (1963) Deterministic equivalents for optimizing and satisficing under chance constraints. Oper Res 11:18–39

    Google Scholar 

  • Charnes A, Cooper WW (1983) Response to “decision problems under risk and chance constrained programming: dilemmas in the transition”. Manage Sci 29(6):750–753

    Google Scholar 

  • Charnes A, Cooper WW et al. (1955) A model for optimizing production by reference to cost surrogates. Econometrica 23(3):307–323

    Google Scholar 

  • Chen HB, Mandelbaum A (1991) Hierarchical modelling of stochastic networks part I: fluid models. In: Yao DD (ed) Stochastic modeling and analysis of manufacturing systems. Springer, New York

    Google Scholar 

  • Cohen JW (1969) The Single server queue. North-Holland, Amsterdam

    Google Scholar 

  • Cohen O (1988) The drum-buffer-rope (DBR) approach to logistics. In: Rolstadas A (ed) Computer-aided production management. Springer, New York

    Google Scholar 

  • Davidson R, MacKinnon JG (1993) Estimation and inference in econometrics. Oxford University Press, New York

    Google Scholar 

  • de Kok AG, Fransoo JC (2003) Planning supply chain operations: definition and comparison of planning concepts. In: de Kok AG, Graves SC (eds) OR Handbook on supply chain management. Elsevier, Amsterdam, pp 597–675

    Google Scholar 

  • Dessouky MM, Leachman RC (1997) Dynamic models of production with multiple operations and general processing times. J Oper Res Soc 48(6):647–654

    Google Scholar 

  • Drexl A, Kimms A (1997) Lot sizing and scheduling – survey and extensions. Eur J Oper Res 99:221–235

    Google Scholar 

  • Elmaghraby SE (1978) The economic lot scheduling problem (ELSP): review and extensions. Manage Sci 24:587–598

    Google Scholar 

  • Eppen G, Martin RK (1988) Determining safety stock in the presence of stochastic lead times. Manage Sci 34:1380–1390

    Google Scholar 

  • Fine CH, Graves SC (1989) A tactical planning model for manufacturing subcomponents of mainframe computers. J Manuf Oper Manage 2:4–34

    Google Scholar 

  • Forrester JW (1962) Industrial dynamics. MIT Press, Cambridge

    Google Scholar 

  • Fredendall LD, Ojha D, Patterson W (2010) Concerning the theory of workload control. Eur J Oper Res 201:99–111

    Google Scholar 

  • Gfrerer H, Zäpfel G (1995) Hierarchical model for production planning in the case of uncertain demand. Eur J Oper Res 86:142–161

    Google Scholar 

  • Graves SC (1981) A review of production scheduling. Oper Res 29(4):646–675

    Google Scholar 

  • Graves SC (1986) A tactical planning model for a job shop. Oper Res 34:552–533

    Google Scholar 

  • Graves SC (1988) Safety stocks in manufacturing systems. J Manuf Oper Manage 1:67–101

    Google Scholar 

  • Gunther HO, Van Beek P (2003) Advanced planning and scheduling solutions in process industry. Springer, Heidelberg

    Google Scholar 

  • Gupta M (2005) Constraints management – recent advances and practices. Int J Prod Res 41(4):647–659

    Google Scholar 

  • Gupta SK, Sengupta JK (1977) Decision rules in production planning under chance-constrained sales. Decision Sci 8:521–533

    Google Scholar 

  • Hackman S (2008) Production economics. Springer, Berlin

    Google Scholar 

  • Hackman ST, Leachman RC (1989) A general framework for modeling production. Manage Sci 35:478–495

    Google Scholar 

  • Hanssmann F, Hess SW (1960) A linear programming approach to production and employment scheduling. Manage Technol 1(1):46–51

    Google Scholar 

  • Harris FW (1915) Operations and cost. Factory management series. Shaw, Chicago

    Google Scholar 

  • Hax AC, Candea D (1984) Production and inventory management. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Haxholdt C, Larsen ER et al. (2003) Mode locking and chaos in a deterministic queueing model with feedback. Manage Sci 49(6):816–830

    Google Scholar 

  • Hendry LC, Kingsman BG (1991) A decision support system for job release in make to order companies. Int J Oper Prod Manage 11:6–16

    Google Scholar 

  • Hogan AJ, Morris JG et al. (1981) Decision problems under risk and chance constrained programming: dilemmas in the transition. Manage Sci 27(6):698–716

    Google Scholar 

  • Holt CC, Modigliani F et al. (1955) A linear decision rule for production and employment scheduling. Manage Sci 2(1):1–30

    Google Scholar 

  • Holt CC, Modigliani F et al. (1956) Derivation of a linear rule for production and employment. Manage Sci 2(2):159–177

    Google Scholar 

  • Holt CC, Modigliani F et al. (1960) Planning production, inventories and work force. Prentice Hall, Englewood Cliffs

    Google Scholar 

  • Hopp WJ, Spearman ML (2001) Factory physics: foundations of manufacturing management. Irwin/McGraw-Hill, Boston

    Google Scholar 

  • Hung YF, Chang CB (1999) Determining safety stocks for production planning in uncertain manufacturing. Int J Prod Econ 58:199–208

    Google Scholar 

  • Hung YF, Cheng GJ (2002) Hybrid capacity modelling for alternative machine types in linear programming production planning. IIE Trans 34:157–165

    Google Scholar 

  • Hung YF, Hou MC (2001) A production planning approach based on iterations of linear programming optimization and flow time prediction. J Chinese Inst Ind Engrs 18(3):55–67

    Google Scholar 

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

    Google Scholar 

  • Hung YF, Wang QZ (1997) A new formulation technique for alternative material planning – an approach for semiconductor bin allocation. Comput Ind Eng 32(2):281–297

    Google Scholar 

  • Hwang S, Uzsoy R (2005) A single stage multi-product dynamic lot sizing model with work in process and congestion. Research report, Laboratory for Extended Enterprises at Purdue, School of Industrial Engineering, Purdue University, West Lafayette

    Google Scholar 

  • Irastorza JC, Deane RH (1974) A loading and balancing methodology for job shop control. AIIE Trans 6(4):302–307

    Google Scholar 

  • Irdem DF, Kacar NB et al. (2008) An experimental study of an iterative simulation-optimization algorithm for production planning. In: Mason SJ, Hill R, Moench L, Rose O (eds) 2008 Winter simulation conference, Miami FL

    Google Scholar 

  • Jackson JR (1955) Scheduling a production line to minimize maximum tardiness. University of California, Los Angeles

    Google Scholar 

  • Jackson JR (1957) Networks of waiting lines. Opeartions Research 10(4):518–521

    Google Scholar 

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

    Google Scholar 

  • Kanet JJ (1988) Load-limited order release in job shop scheduling systems. J Oper Manage 7:413–422

    Google Scholar 

  • Karmarkar US (1987) Lot sizes, lead times and in-process inventories. Manage Sci 33(3):409–418

    Google Scholar 

  • Karmarkar US (1989) Capacity loading and release planning with work-in-progress (WIP) and lead-times. J Manufac Oper Manage 2:105–123

    Google Scholar 

  • Karmarkar US (1993) Manufacturing lead-times, order release and capacity loading. In: Graves SC, Rinnooy Kan AHG, Zipkin PH (eds) Logistics of production and inventory. Handbooks in operations research & management science, vol. 4. North-Holland, Amsterdam, pp 287–329

    Google Scholar 

  • Karmarkar US, Kekre S et al. (1985a) Lotsizing in multimachine job shops. IIE Trans 13(3): 290–298

    Google Scholar 

  • Karmarkar US, Kekre S et al. (1985b) Lot sizing and lead time performance in a manufacturing cell. Interfaces 15(2):1–9

    Google Scholar 

  • Kekre S (1984) The effect of number of items processed at a facility on manufacturing lead time. Working paper series. University of Rochester, Rochester

    Google Scholar 

  • Kekre S (1987) Performance of a manufacturing cell with increased product mix. IIE Trans 19(3):329–339

    Google Scholar 

  • Kim B, Kim S (2001) Extended model for a hybrid production planning approach. International J Prod Econ 73:165–173

    Google Scholar 

  • Kim JS, Leachman RC (1994) Decomposition method application to a large scale linear programming WIP projection model. Eur J Oper Res 74:152–160

    Google Scholar 

  • Kim JS, Leachman RC et al. (1996) Dynamic release control policy for the semiconductor wafer fabrication lines. J Oper Res Soc 47(12):1516–1525

    Google Scholar 

  • Kistner KP (1999) Lot sizing and queueing models: some remarks on Karmarkar’s model. In: Leopold-Wildburger U, Feichtinger G, Kistner HP (eds) Modelling and Decisions in Economics: Essays in Honor of Franz Ferschl. Physica, Heidelberg, pp 173–188

    Google Scholar 

  • Kleinrock L (1976) Queueing systems volume II: computer system applications. Wiley, New York

    Google Scholar 

  • Koopmans T (ed) (1951) Activity analysis of production and allocation. Wiley, New York

    Google Scholar 

  • Krämer W, Langenbach-Belz M (1976) Approximate formulae for the delay in queueing system GI/G/1. 8th International telegraphic congress. Melbourne, pp 235/1–235/8

    Google Scholar 

  • Lambrecht MR, Chen S et al. (1996) A Lot sizing model with queueing delays: the issue of safety time. Eur J Oper Res 89:269–276

    Google Scholar 

  • Lambrecht MR, Luyten R et al. (1984a) Protective inventories and bottlenecks in production systems. Eur J Oper Res 22:319–328

    Google Scholar 

  • Lambrecht MR, Muckstadt JA et al. (1984b) Protective stocks in multi-stage production systems. Int J Prod Res 22:1001–1025

    Google Scholar 

  • Land M (2004) Workload control in job shops, grasping the tap. Labyrinth, Ridderkerk

    Google Scholar 

  • Lasserre JB, Mercé C (1990) Robust hierarchical production planning under uncertainty. Ann Oper Res 26(4):73–87

    Google Scholar 

  • Lautenschläger M (1999) Mittelfristige Produktionsprogrammplanung mit auslastungsabhängigen Vorlaufzeiten. Peter Lang, Frankfurt am Main

    Google Scholar 

  • Lautenschläger M, Stadtler H (1998) Modelling lead times depending on capacity utilization. Research report, Technische Universitat Darmstadt

    Google Scholar 

  • Leachman RC (1993) Modeling techniques for automated production planning in the semiconductor industry. In: Ciriani TA, Leachman RC (eds) Optimization in industry: mathematical programming and modelling techniques in practice. Wiley, New York, pp 1–30

    Google Scholar 

  • Leachman RC, Benson RF et al. (1996) IMPReSS: an automated production planning and delivery quotation system at Harris corporation – semiconductor sector. Interfaces 26:6–37

    Google Scholar 

  • Leachman RC, Carmon TF (1992) On capacity modeling for production planning with alternative machine types. IIE Trans 24(4):62–72

    Google Scholar 

  • Lejeune MA, Prekopa A (2005) Approximations for and convexity of probabilistically constrained problems with random right hand sides. RUTCOR research report. Rutgers University, New Jersey

    Google Scholar 

  • Liu L, Liu X et al. (2004) Analysis and optimization of multi-stage inventory queues. Manage Sci 50:365–380

    Google Scholar 

  • Lu S, Ramaswamy D et al. (1994) Efficient scheduling policies to reduce mean and variance of cycle time in semiconductor plants. IEEE Trans Semicond Manufac 7:374–388

    Google Scholar 

  • Luss H (1982) Operations research and capacity expansion problems: a survey. Oper Res 30(5):907–947

    Google Scholar 

  • Manne AS (1957) A note on the Modigliani-Hohn production smoothing model. Manage Sci 3(4):371–379

    Google Scholar 

  • Manne AS (1960) On the job-shop scheduling problem. Oper Res 8(2):219–223

    Google Scholar 

  • Medhi J (1991) Stochastic models in queuing theory. Academic, Amsterdam

    Google Scholar 

  • Merchant DK, Nemhauser GL (1978a) A model and an algorithm for the dynamic traffic assignment problems. Transp Sci 12(3):183–199

    Google Scholar 

  • Merchant DK, Nemhauser GL (1978b) Optimality conditions for a dynamic traffic assignment model. Transp Sci 12(3):200–207

    Google Scholar 

  • Missbauer H (1997) Order release and sequence-dependent setup times. Int J Prod Econ 49:131–143

    Google Scholar 

  • Missbauer H (1998) Bestandsregelung als Basis für eine Neugestaltung von PPS-Systemen. Physica, Heidelberg

    Google Scholar 

  • Missbauer H (1999) Die Implikationen durchlauforientierter Losgrößenbildung für die Komplexität der Produktionsplanung und –steuerung. Zeitschrift für Betriebswirtschaft 69(2): 245–265

    Google Scholar 

  • Missbauer H (2002a) Aggregate order release planning for time-varying demand. Int J Prod Res 40:688–718

    Google Scholar 

  • Missbauer H (2002b) Lot sizing in workload control systems. Prod Plan Control 13:649–664

    Google Scholar 

  • Missbauer H (2009) Models of the transient behaviour of production units to optimize the aggregate material flow. Int J Prod Econ 118(2):387–397

    Google Scholar 

  • Missbauer H (forthcoming) Order release planning with clearing functions: a queueing-theoretical analysis of the clearing function concept. Int J Prod Econ

    Google Scholar 

  • Missbauer H, Hauber W et al. (forthcoming). Developing a computerized scheduling system for the steelmaking - continuous casting process. In: Kempf KG, Keskinocak P, Uzsoy R (eds) Planning in the extended enterprise: a state of the art handbook. Springer, New York

    Google Scholar 

  • Modigliani F, Hohn FE (1955) Production planning over time and the nature of the expectation and planning horizon. Econometrica 23(1):46–66

    Google Scholar 

  • Neuts MF (1981) Matrix-geometric solutions in stochastic models. Johns Hopkins University Press, Baltimore

    Google Scholar 

  • Nyhuis P, Wiendahl HP (2003) Logistische Kennlinien. Springer, Berlin

    Google Scholar 

  • Orcun S, Uzsoy R et al. (2006) Using system dynamics simulations to compare capacity models for production planning. Winter simulation conference. Monterey, CA

    Google Scholar 

  • Orlicky J (1975) Material requirements planning: the new way of life in production and inventory management. McGraw-Hill, New York

    Google Scholar 

  • Pahl J, Voss S et al. (2005) Production planning with load dependent lead times. 4OR 3:257–302

    Google Scholar 

  • Parker RG (1995) Deterministic scheduling theory. Chapman and Hall, London

    Google Scholar 

  • Parrish SH (1987) Extensions to a model for tactical planning in a job shop environment. Operations Research Center. Massachusetts Institute of Technology, Cambridge, MA

    Google Scholar 

  • Peeta S, Ziliaskopoulos AK (2001) Foundations of dynamic traffic assignment: the past, the present and the future. Network Spatial Econ 1(3–4):233–265

    Google Scholar 

  • Perona M, Portioli A (1998) The impact of parameters setting in load oriented manufacturing control. Int J Prod Econ 55(133–142)

    Google Scholar 

  • Peters RJ, Boskma K et al. (1977) Stochastic programming in production planning: a case with non-simple recourse. Statistica Neerlandica 31:113–126

    Google Scholar 

  • Philipoom RR, Fry TD (1992) Capacity based order review/release strategies to improve manufacturing performance. Int J Prod Res 30:2559–2572

    Google Scholar 

  • Pinedo M (1995) Scheduling theory, algorithms, and systems. Prentice-Hall, New Jersey

    Google Scholar 

  • Pinedo M, Chao X (2005) Planning and scheduling in manufacturing and services. Springer, New York

    Google Scholar 

  • Powell SG, Schultz KL (2004) Throughput in serial lines with state-dependent behaviour. Manage Sci 50(8):1095–1105

    Google Scholar 

  • Prekopa A (1993) Programming under probabilistic constraint and maximizing a probability under constraints. Center for operations Research, Rutgers University, New Brunswick

    Google Scholar 

  • Rakes TR, Franz LS et al. (1984) Aggregate production planning using chance-constrained goal programming. Int J Prod Res 22(4):673–684

    Google Scholar 

  • Riaño G (2003) Transient behavior of stochastic networks: application to production planning with load-dependent lead times. School of Industrial and Systems Engineering. Georgia Institute of Technology, Atlanta

    Google Scholar 

  • Riaño G, Hackman S et al. (2006) Transient behavior of queueing networks. School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta

    Google Scholar 

  • Riaño G, Serfozo R et al. (2003) Benchmarking of a stochastic production planning model in a simulation testbed. Winter simulation conference

    Google Scholar 

  • Schneeweiß C (2003) Distributed decision making. Springer, Berlin

    Google Scholar 

  • Selçuk B (2007) Dynamic performance of hierarchical planning systems: modeling and evaluation with dynamic planned lead times. Technische Universiteit Eindhoven, Eindhoven

    Google Scholar 

  • Selçuk B, Fransoo JC et al. (2007) Work in process clearing in supply chain operations planning. IIE Trans 40:206–220

    Google Scholar 

  • Sengupta JK (1972) Decision rules in stochastic programming under dynamic economic models. Swed J Econ 74:370–389

    Google Scholar 

  • Sengupta JK, Portillo-Campbell JH (1973) A reliability programming approach to production planning. Int Stat Rev 41:115–127

    Google Scholar 

  • Singhal J, Singhal K (2007) Holt, Modigliani, Muth and Simon’s work and its role in the renaissance and and evolution of operations management. J Oper Manage 25:300–309

    Google Scholar 

  • Smith SF (1993) Knowledge-based production management: approaches, results and prospects. Prod Plan Control 3(4):350–380

    Google Scholar 

  • Spearman ML (1991) An analytic congestion model for closed production systems with IFR processing times. Manage Sci 37(8):1015–1029

    Google Scholar 

  • Spearman ML, Woodruff DL et al. (1990) CONWIP: a pull alternative to Kanban. Int J Prod Res 28(5):879–894

    Google Scholar 

  • Spitter JM, de Kok AG et al. (2005a) Timing production in LP models in a rolling schedule. Int J Prod Econ 93–94:319–329

    Google Scholar 

  • Spitter JM, Hurkens CAJ et al. (2005b) Linear programming models with planned lead times for supply chain operations planning. Eur J Oper Res 163:706–720

    Google Scholar 

  • Srinivasan A, Carey M et al. (1988) Resource pricing and aggregate scheduling in manufacturing systems. Graduate School of Industrial Administration, Carnegie-Mellon University, Pittsburgh

    Google Scholar 

  • Stadtler H (1996) Hierarchische Produktionsplanung. Handwörterbuch der Produktionswirtschaft. Schäffer-Poeschel, Stuttgart, pp 631–641

    Google Scholar 

  • Stadtler H, Kilger C (eds) (2008) Supply chain management and advanced planning: concepts, models, software and case studies. Springer-Verlag, Berlin

    Google Scholar 

  • Stange K (1964) Die Anlauflösung für den einfachen exponentiellen Bedienungskanal (mit beliebig vielen Warteplätzen), der für t=0 leer ist. Unternehmenforschung 8:1–24

    Google Scholar 

  • Stevenson M, Hendry LC (2006) Aggregate load-oriented workload control: a review and a re-classification of a key approach. Int J Prod Econ 104(2):676–693

    Google Scholar 

  • Tang L, Liu J et al. (2001) A review of planning and scheduling systems and methods for integrated steel production. Eur J Oper Res 133:1–20

    Google Scholar 

  • Tardif V, Spearman ML (1997) Diagnostic scheduling in finite-capacity production environments. Comput Ind Eng 32:867–878

    Google Scholar 

  • Tatsiopoulos IP, Kingsman BP (1983) Lead time management. Eur J Oper Res 14:351–358

    Google Scholar 

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

    Google Scholar 

  • Uzsoy R, Lee CY et al. (1994) A review of production planning and scheduling models in the semiconductor industry part II: shop-floor control. IIE Trans Scheduling Logistics 26:44–55

    Google Scholar 

  • Van Ooijen HPG (1996) Load-based work-order release and its effectiveness on delivery performance improvement. Eindhoven University of Technology, Eindhoven

    Google Scholar 

  • Van Ooijen HPG, Bertrand JWM (2003) The effects of a simple arrival rate control policy on throughput and work-in-process in production systems with workload dependent processing rates. Int J Prod Econ 85(1):61–68

    Google Scholar 

  • Vaughan TS (2006) Lot size effects on process lead time, lead time demand, and safety stock. Int J Prod Econ 100:1–9

    Google Scholar 

  • Vepsalainen AP, Morton TE (1987) Priority rules for job shops with weighted tardiness costs. Manage Sci 33(8):1035–1047

    Google Scholar 

  • Vepsalainen AP, Morton TE (1988) Improving local priority rules with global lead-time estimates: a simulation study. J Manufac Oper Manage 1:102–118

    Google Scholar 

  • Vollmann TE, Berry WL et al. (1988) Manufacturing planning and control systems. Richard D. Irwin, Boston

    Google Scholar 

  • Vollmann TE, Berry WL et al. (2005) Manufacturing planning and control for supply chain management. McGraw-Hill, New York

    Google Scholar 

  • Voss S, Woodruff DL (2003) 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 dynamic version of the economic lot size model. Manage Sci 5:89–96

    Google Scholar 

  • Wiendahl HP (1995) Load oriented manufacturing control. Springer, Heidelberg

    Google Scholar 

  • Wight O (1983) MRPII: unlocking America’s productivity potential. Oliver Wight, Williston

    Google Scholar 

  • Wijngaard J, Wortmann JC (1985) MRP and inventories. Eur J Oper Res 20:281–293

    Google Scholar 

  • Yano CA, Carlson RC (1988) Safety stocks for assembly systems with fixed production intervals. J Manufac Oper Manage 1:182–201

    Google Scholar 

  • Zäpfel G, Missbauer H (1993a) Production planning and control (PPC) systems including load-oriented order release – problems and research perspectives. Int J Prod Econ 30:107–122

    Google Scholar 

  • Zäpfel G, Missbauer H (1993b) New concepts for production planning and control. Eur J Oper Res 67:297–320

    Google Scholar 

  • Zäpfel G, Missbauer Hetal.(1992)PPS-Systeme mit belastungs orientierter Auftragsfreigabe– Operationscharakteristika und Möglichkeiten zur Weiterentwicklung. Zeitschrift für Betriebswirtschaft 62:897–919

    Google Scholar 

  • Zipkin PH (1986) Models for design and control of stochastic, multi-item batch production systems. Oper Res 34(1):91–104

    Google Scholar 

  • Zipkin PH (1997) Foundations of inventory management. Irwin, Burr Ridge

    Google Scholar 

  • Zweben M, Fox M (eds) (1994) Intelligent scheduling systems. Morgan Kaufman, San Francisco

    Google Scholar 

Download references

Acknowledgments

The research of Reha Uzsoy was supported by the National Science Foundation under Grant DMI-0556136, by the Intel Research Council, by a software grant from Dash Optimization and an equipment grant from Intel Corporation.

Author information

Authors and Affiliations

  1. Department of Information Systems, Production and Logistics Management, University of Innsbruck, Universitätstrasse 15, Innsbruck, A-6020, Austria

    Reha Uzsoy

Authors
  1. Hubert Missbauer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reha Uzsoy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Reha Uzsoy .

Editor information

Editors and Affiliations

  1. Decision Technologies, Intel Corporation, W. Chandler Blvd. 5000, Chandler, 85226, Arizona, USA

    Karl G. Kempf

  2. School of Industrial &, Systems Engineering, Georgia Institute of Technology, Ferst Drive NW., 765, Atlanta, 30332-0205, Georgia, USA

    Pınar Keskinocak

  3. , Edward P. Fitts Department of Industrial, North Carolina State University, Daniels Hall 300, Raleigh, 27695, North Carolina, USA

    Reha Uzsoy

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Missbauer, H., Uzsoy, R. (2011). Optimization Models of Production Planning Problems. In: Kempf, K., Keskinocak, P., Uzsoy, R. (eds) Planning Production and Inventories in the Extended Enterprise. International Series in Operations Research & Management Science, vol 151. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6485-4_16

Download citation

Publish with us

Policies and ethics

Search

Navigation