Skip to main content
Log in

SAINC: self-adapting inventory control decision support system for cement industries

  • Original Paper
  • Published:
Operational Research Aims and scope Submit manuscript

Abstract

Most of the software systems developed to support the inventory control process for modern industrial units are based on the common economic order quantity models (EOQ) and they utilise parameters, which are estimated either empirically or through some kind of statistical process regarding the transactions of materials for a particular time period. This research work deals with the development of an integrated decision support system, the SAINC system, for decisions related to the inventory control for cement industries. The proposed system is characterised by its capability to: (a) treat large volume of data in real time; (b) estimate inventory control parameters’ values in real time by taking into consideration all the significant factors; (c) support decisions that concern the inventory control at a tactical and strategic level; and (d) cooperate with any information system for logistics management.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Billington C, Davis T (1992) Manufacturing strategy analysis: models and practice. OMEGA 20(5/6):587–595

    Article  Google Scholar 

  • Borgonovo E, Peccati L (2007) Global sensitivity analysis in inventory management. Int J Prod Econ 108(1–2):302–313

    Article  Google Scholar 

  • Chung K-J, Huang T-S (2007) The optimal retailer’s ordering policies for deteriorating items with limited storage capacity under trade credit financing. Int J Prod Econ 106(1):127–145

    Article  Google Scholar 

  • Davis T (1993) Effective supply chain management. Sloan Manage Rev 34(4):35–46

    Google Scholar 

  • Ehrhard R (1984) Policies for a dynamic inventory model with stochastic lead time. Oper Res 32(1):121–132

    Article  Google Scholar 

  • Eynan A, Kropp DH (2007) Effective and simple EOQ-like solutions for stochastic demand periodic review systems. Eur J Oper Res 180(3):1135–1143

    Article  Google Scholar 

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

    Google Scholar 

  • Hawkins H (1998) Data warehousing architecture and implementation, 1st edn. Prentice–Hall PTR, Englewood Cliffs

    Google Scholar 

  • Johnson ME, Lee H, Davis T, Hall R (1995) Expressions for item fill rates in periodic inventory systems. Naval Res Logistics 42(1):57–80

    Article  Google Scholar 

  • Jung H, Klein CM (2006) Optimal inventory policies for profit maximizing EOQ models under various cost functions. Eur J Oper Res 174(2):689–705

    Article  Google Scholar 

  • Jung H, Klein CM (2005) Optimal inventory policies for an economic order quantity model with decreasing cost functions. Eur J Oper Res 165(1):108–126

    Article  Google Scholar 

  • Lee H, Billington C, Carter B (1993) Hewlett–Packard gains control of inventory and service through design for localization. Interfaces 23(4):1–11

    Article  Google Scholar 

  • Luenberger DG (1984) Linear and nonlinear programming. Addison-Wesley, Reading

    Google Scholar 

  • Malach EG (2000) Decision support and data warehouse systems. McGraw-Hill, New York

    Google Scholar 

  • Min KJ, Chen C-K (1995) A competitive inventory model with options to reduce setup and inventory holding costs. Comput Oper Res 22(5):503–514

    Article  Google Scholar 

  • Nahmias S (2001) Inventory control subject to uncertain demand, production and operations analysis, 4th edn. McGraw-Hill, Irwin, pp 243–304

    Google Scholar 

  • Siskos Y, Spyridakos A (1999) Intelligent multicriteria decision support: overview and perspectives. Eur J Oper Res 113:236–246

    Article  Google Scholar 

  • Silver EA, Peterson R (1985) Decision systems for inventory management and production planning. Wiley, New York

    Google Scholar 

  • Swenseth SR, Godfrey MR (2002) Incorporating transportation costs into inventory replenishment decisions. Int J Prod Econ 77(2–21):113–130

    Article  Google Scholar 

  • Turban E (1993) Decision support and expert systems: management support systems, 3rd edn. McMillan, New York

  • Turban E, Aronson JR, Liang TP (2004) Decision support systems and intelligent systems, 7th edn. Prentice–Hall, Englewood Cliffs

  • Wagner HM (1975) Principles of operations research. Prentice–Hall, New York

    Google Scholar 

  • Winston W, Albright SC (2001) Practical management science, Chap.~13, Duxbury Press, North Scituate

  • Yu G (1997) Robust economic order quantity models. Eur J Oper Res 100(3):482–493

    Article  Google Scholar 

  • Zangwill W (1992) The limits of japanese production theory. Interfaces 22(5):14–25

    Article  Google Scholar 

  • Zhao Q-H, Wang S-Y, Lai K-K, Xia G-P (2004) Model and algorithm of an inventory problem with the consideration of transportation cost. Comput Ind Eng 46(2):389–397

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Athanasios Spyridakos.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Spyridakos, A., Tsotsolas, N., Mellios, J. et al. SAINC: self-adapting inventory control decision support system for cement industries. Oper Res Int J 9, 183–198 (2009). https://doi.org/10.1007/s12351-008-0017-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12351-008-0017-3

Keywords

Mathematics Subject Classification (2000)

Navigation