109
Views
5
CrossRef citations to date
0
Altmetric
General Paper

Forecasting of compound Erlang demand

, &
Pages 2061-2074 | Received 18 Feb 2014, Accepted 11 Mar 2015, Published online: 21 Dec 2017

References

  • AltayNLitteralLAService Parts Management: Demand Forecasting and Inventory Control (Handbook)2011
  • AxsäterSInventory Control2006
  • BartezzaghiEVergantiRZotteriGA simulation framework for forecasting uncertain lumpy demandInternational Journal of Production Economics1999591–349951010.1016/S0925-5273(98)00012-7
  • BBC (British Broadcasting Corporation) (2013). Communication, http://www.bbc.co.uk/news/uk-politics-21608747, accessed on 3 April 2015.
  • BoylanJESyntetosAASpare parts management: A review of forecasting research and extensionsIMA Journal of Management Mathematics201021322723710.1093/imaman/dpp016
  • BoylanJESyntetosAAKarakostasGCClassification for forecasting and stock control: A case studyJournal of the Operational Research Society200859447348110.1057/palgrave.jors.2602312
  • BrownRGStatistical Forecasting for Inventory Control1959
  • BrownRGSmoothing, Forecasting and Prediction of Discrete Time Series1963
  • BurginTAWildARStock control experience and usable theoryOperational Research Quarterly1967181355210.1057/jors.1967.4
  • ChatfieldCGoodhardtGJA consumer purchasing model with Erlang inter-purchase timesJournal of the American Statistical Association197340344828835
  • ChewEPJohnsonLAService levels in distribution systems with random customer order sizeNaval Research Logistics2006421395610.1002/1520-6750(199502)42:1<39::AID-NAV3220420106>3.0.CO;2-9
  • CoxDRRenewal Theory1962
  • CrostonJDForecasting and stock control for intermittent demandsOperational Research Quarterly197223328930310.1057/jors.1972.50
  • Dawson P (2013). Managing Director, DBO Services. http://www.dboservices.com/, assessed on 3 April 2015. Private communications to the corresponding author.
  • Deloitte (2006). The service revolution in global manufacturing industries. New York: Deloitte Research, http://www.apec.org.au/docs/2011-11_training/deloitte2006.pdf, accessed on 3 April 2015.
  • DMO (Defence Materiel Organisation) (2010). Australian Government, Department of Defence, Fact Sheet. http://www.defence.gov.au/dmo/asr/ss/Fact_sheet_Feb10.pdf, accessed on 18 April 2013.
  • EavesAHCKingsmanBGForecasting for the ordering and stockholding of spare partsJournal of the Operational Research Society200455443143710.1057/palgrave.jors.2601697
  • FildesRNikolopoulosKCroneSSyntetosAAForecasting and operational research: A reviewJournal of the Operational Research Society20085991150117210.1057/palgrave.jors.2602597
  • GAO (United States General Accounting Office) (1999). Defense inventory: continuing challenges in managing inventories and avoiding adverse operational effects, GAO/T-NSIAD-99-83, Washington DC, February 25. http://www.gao.gov/products/GAO/T-NSIAD-99-83, accessed on 3 April 2015.
  • GAO (United States General Accounting Office) (2011). DOD’s inventory management improvement plan, GAO-11-240 R, Washington DC, 7 January. http://www.gao.gov/products/GAO-11-240R, accessed on 3 April 2015.
  • GAO (United States General Accounting Office) (2012). Defense inventory: actions underway to implement improvement plan, but steps needed to enhance effort, GAO-12-493, Washington DC, 3 May. http://www.gao.gov/products/GAO-12-493, accessed on 3 April 2015.
  • Gardner Jr. ES (2011). Forecasting for operations, Keynote. International Symposium on Forecasting (ISF), Prague, Czech Republic.
  • GhobbarAAFriendCHSources of intermittent demand for aircraft spare parts within airline operationsJournal of Air Transport Management20028422123110.1016/S0969-6997(01)00054-0
  • GravesSCA single-item inventory model for a nonstationary demand processManufacturing and Service Operations Management199911506110.1287/msom.1.1.50
  • Herniter JD (1970). Probabilistic market models of purchase timing and brand selection. Working Paper, Marketing Science Institute, Cambridge, MA.
  • JohnstonFRBoylanJEForecasting for items with intermittent demandJournal of the Operational Research Society199647111312110.1057/jors.1996.10
  • JohnstonFRBoylanJEShaleEAAn examination of the size of orders from customers, their characterization and the implications for inventory control of slow moving itemsJournal of the Operational Research Society200354883383710.1057/palgrave.jors.2601586
  • LariviereMAvan MieghemJAStrategically seeking service: How competition can generate poisson arrivalsManufacturing and Service Operations Management200461234010.1287/msom.1030.0030
  • Larsen C (2008). A note on Poisson and Erlang processes. Working paper, Cluster of Operational Research and Logistics (CORAL), Department of Economics and Business, Aarhus University, Denmark.
  • LarsenCSeidingHGTellerCThorstensonAAn inventory control project in a major Danish company using compound renewal demand modelsIMA Journal of Management Mathematics200819214516210.1093/imaman/dpm036
  • LarsenCThorstensonAA comparison between the order and the volume fill rate for a base-stock inventory control system under a compound renewal demand processJournal of the Operational Research Society200859679880410.1057/palgrave.jors.2602407
  • Morse A (2012). Ministry of defence: managing the defence inventory, National Audit Office (NAO), UK, 2012. http://www.nao.org.uk/report/managing-the-defence-inventory/, accessed on 3 April 2015.
  • RegattieriAGamberiMGamberiniRManziniRManaging lumpy demand for aircraft spare partsJournal of Air Transport Management200511642643110.1016/j.jairtraman.2005.06.003
  • RossSMStochastic Processes1996
  • ScalaNMRajgopalJNeedyKLSA base stock inventory management system for intermittent spare partsMilitary Operations Research2013183637710.5711/1082598318363
  • ScalaNMRajgopalJNeedyKLSManaging nuclear spare parts inventories: A data driven methodologyIEEE Transactions on Engineering Management2014611283710.1109/TEM.2013.2283170
  • ShaleEABoylanJEJohnstonFRForecasting for intermittent demand: The estimation of an unbiased averageJournal of the Operational Research Society200657558859210.1057/palgrave.jors.2602031
  • SmithMAJDekkerROn the (S−1, S) stock model for renewal demand processesProbability in the Engineering and Informational Sciences199711337538610.1017/S0269964800004897
  • StrijboschLWGHeutsRMJvan der SchootEHMA combined forecast-inventory control procedure for spare partsJournal of the Operational Research Society200051101184119210.2307/253931
  • SyntetosAABabaiMZDalleryYTeunterRPeriodic control of intermittent demand items: Theory and empirical analysisJournal of the Operational Research Society200960561161810.1057/palgrave.jors.2602593
  • Syntetos AA, Babai MZ and Gardner Jr. ES (2015). Forecasting intermittent inventory demands: Parametric methods VS. Bootstrapping. Journal of Business Research,. in press.
  • SyntetosAABoylanJEOn the bias of intermittent demand estimatesInternational Journal of Production Economics2001711–345746610.1016/S0925-5273(00)00143-2
  • SyntetosAABoylanJEThe accuracy of intermittent demand estimatesInternational Journal of Forecasting200521230331410.1016/j.ijforecast.2004.10.001
  • SyntetosAABoylanJEOn the stock-control performance of intermittent demand estimatorsInternational Journal of Production Economics20061031364710.1016/j.ijpe.2005.04.004
  • SyntetosAABoylanJEOn the variance of intermittent demand estimatesInternational Journal of Production Economics2010128254655510.1016/j.ijpe.2010.07.005
  • SyntetosAABoylanJECrostonJDOn the categorization of demand patternsJournal of the Operational Research Society200556549550310.1057/palgrave.jors.2601841
  • SyntetosAABoylanJEDisneySMForecasting for inventory planning: A 50-year reviewJournal of the Operational Research Society200960S114916010.1057/jors.2008.173
  • TeunterRSyntetosAABabaiMZIntermittent demand: Linking forecasting to inventory obsolescenceEuropean Journal of Operational Research2011214360661510.1016/j.ejor.2011.05.018
  • TrabkaEAMarchandEWMean and variance of the number of renewals of a censored Poisson processBiological Cybernetics197076221224
  • WatsonRBThe effects of demand-forecast fluctuations on customer service and inventory costs when demand is lumpyJournal of the Operational Research Society1987381758210.1057/jors.1987.9
  • Ziotopoulou D (2009). Review and analysis of information systems NEMES and PYTHIA for intermittent demand time series forecasting. BSc dissertation, National Technical University of Athens, Greece.
  • ZipkinPHFoundations of Inventory Management2000

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.