Inventory Control and Management

Instructor:     

 

Andrey V. ZyatchinCan.Sc., Associate Professor, Department of Operations Management, Graduate School of Management, St Petersburg University

Workload:

6 ECTS, 45 contact hours

 

Prerequisites:

Probability theory, Statistics, Operations research, Logistics and Supply Chain Management

 

Aim of the Course:   

 

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.

 

Course Content:       

 

Topic 1. Foundations of inventory management

Сhapter 1.1  Introduction to inventory management

Сhapter 1.2 Classification of inventory management models

Сhapter 1.3 q and p systems

Сhapter 1.4 АВС, XYZ, VED, FNSD analysis

 

Topic 2. Deterministic inventory management models

Сhapter 2.1 The economic order quantity model

Сhapter 2.2 The economic order quantity model with quantity discount

Сhapter 2.3 Backorders

Сhapter 2.4 Networks in inventory management. Vehicle routing problem, the shortest path and the maximum flow problem 

 

Topic 3. Dynamic models in inventory management Time-varying demands

Сhapter 3.1 Classification of dynamic models in inventory management

Сhapter 3.2 The dynamic economic lot size model

Сhapter 3.3 Network representation, heurisitic and optimal solution to the dynamic economic lot size model

 

Topic 4. Inventory management models under uncertainty

Сhapter 4.1 Classification of inventory management models under uncertainty

Сhapter 4.2 Newspaper boy problem

Сhapter 4.3 Buffer stock

Сhapter 4.4 Inventory model with uncertainty in demand and leadtime

Сhapter 4.5 Inventory within supply chain management

 

 

Teaching methods:   

 

Lectures, group projects, cases, quantitative optimization models and their realization in MS Excel, individual and group presentations

 

 

Literature: 

 


Compulsory literature 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)

 

Supplementary literature list

  • 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

 


 

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