Inventory control and management (ICM) being a part of logistics management is in general about specifying the size and placement of stocked goods. It is required at different locations within a facility or within multiple locations of a supply network to protect the regular and planned course of production against the random disturbance of running out of materials or goods.
The scope of ICM also concerns the fine lines between replenishment lead time, carrying costs of inventory, asset management, inventory forecasting, inventory valuation, inventory visibility, future inventory price forecasting, physical inventory, available physical space for inventory, returns and defective goods and demand forecasting. Balancing these competing requirements leads to optimal inventory levels, which is an on-going process as the business needs shift and react to the wider environment.
The goal of the course is to introduce students to the formulation, analysis and using of mathematical models and optimization technique in inventory system.
- Students know classification of inventory management models.
- Students get skills of inventory management in deterministic and stochastic cases.
- Students can find optimal solution and provide a sensitivity analysis in the common models of inventory management.
- Students can use software for networking and inventory management problems solving.
Course Reading (the full list):
• Davis R.A. 2013 Demand-Driven Inventory Optimization and Replenishment: Creating a More Efficient Supply Chain, John Wiley & Sons (available on Ebrary Academic Complete)
• Relph G, Milner C. 2015 Inventory Management: Advanced Methods for Managing Inventory within Business Systems, KoganPage 2nd Floor, 45 Gee Street London EC1V 3RS United Kingdom (available on Books24x7)
• Abuhilal, L., Rabadi, G. and Sousa-Poza, A. (2006). Supply Chain Inventory Control: A Comparison Among JIT, MRP, and MRP With Information Sharing Using Simulation // Engineering Management Journal, Vol. 18 Issue 2, p. 51-57
• Axsäter, S. (2006) Inventory Control, Springer, New York (2nd edition).
• Clarke G., Wright J.W. (1964). Scheduling of vehicles from a central depot to a number of delivery points // Operations Research, vol. 12 no. 4 pp. 568-581
• Graves S., Rinnooy A., and P. Zipkin (eds.) (1993) Logistics of Production and Inventory. Handbooks in Operations Research and Management Science, Volume 4, North-Holland, Amsterdam.
• Janssens, G., Ramaekers, K., (2011). A linear programming formulation for an inventory management decision problem with a service constraint. // Expert Systems with Applications, Vol. 38 Issue 7, p7929-7934,
• de Kok, A. and S. Graves (eds.) (2003) Supply Chain Management. Handbooks in Operations Research and Management Science, Volume 30, North-Holland, Amsterdam.
• Porteus, E. (2002) Foundations of Stochastic Inventory Theory, Stanford U. Press, Stanford, CA.
• Muller, M. (2011) Essentials of Inventory Management, Second Edition, AMACOM New York, NY.
• Ramamurthy P. 2007. Operations Research, New Age International (available on Ebrary Academic Complete)
• Schutt J. (2004) Directing the Flow of Product: A Guide to Improving Supply Chain Planning, J. Ross Publishing J. Ross Publishing.
• Simchi-Levi, D., Wu S. and M. Shen (2004) Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era, Kluwer, Norwell, MA.
• Taha, H. (2002). Operations Research: An Introduction
• Tayur, S., R. Ganeshan and M. Magazine (1999) Quantitative Models for Supply Chain Management, Kluwer, Norwell, MA.
• Viale D. (1996). Basics of inventory management, Von Hoffman graphics.
• Wild, T. (2002). Best Practice in Inventory management, Butterworth-Heinemann, Linacre House, Jordan Hill, Oxford
• Zipkin P. 2000. Foundations of Inventory Management, McGraw-Hill Education