Inventory Management

Standard inventory control models and approaches are presented for single- and multi-period dynamic inventory models, multi-echelon models, and multi-product coordinated replenishment problems. Further, different approaches to data driven inventory policies are presented that address the estimation and analysis of model parameters. Case studies and board games are used to motivate these concepts. Specifically, the module covers the topics: • Performance metrics; • Lot sizing: EOQ, EPQ, Wagner Whitin; • Forecasting: Time series, regression, data analysis, probability distributions; • Newsvendor model; • Single echelon inventory control: (R,S), (s,Q)policies and parameter optimization; • Multi echelon inventory control: Concepts, lot sizing, safety stock optimization, METRIC; • Multiproduct models: ELSP, CLSP, DLSP, CSLP, PLSP; • Warehouse scheduling, joint replenishment problems; • Multi location problems; • Sport Obermeyer Case and MIT Beer Distribution Game; • Special topics: Perishable items, multi supplier models, lost sales models

The participants will learn about different concepts in Inventory management and receive the knowledge to apply decision support tools for an effective design and operation of inventory management systems. They will be able to memorize different inventory control rules, identify the right model in different industry environment and be able to reproduce parameter calculations. They will be able to illustrate the impact of cost and service parameters on timing and sizes of replenishment decisions and generalize these finding to more complex multi-echelon and multi- product systems. This fundamental knowledge will enable participants to evaluate, compare and optimize different control systems, revise parameter settings and critically reflect on optional choices. Upon completion of this module, the participants will be able to develop and implement models and methods for new and innovative inventory management problems, e.g. arising in same-day home delivery, car-sharing or reverse logistics applications.

The grading is based on a written exam (90 minutes) consisting of 4 questions, the participants can choose 3 out of 4. Each question has several parts assessing the different competence levels. In a first theory part, the student has to reproduce knowledge about inventory management concepts. In a second part, different calculation methods need to be applied with given data and the results be analyzed and interpreted. In a third part, the students need to develop ideas and concepts beyond the reproduction of knowledge and application of methods. In order to facilitate calculations and for backup of some statistical formulas, a formula sheet and a pocket calculator can be used.

The module requires basic knowledge in statistics (discrete and continuous probability distributions) and Excel and the course “Modelling, Optimization, and Simulation” due to extensive use of Mixed-Integer Programming and Simulation methods.

The module includes lectures where students obtain knowledge about inventory modeling and optimization techniques. In exercise sessions, the students solve problems with the obtained knowledge, perform optimizations and simulations, interpret the findings and present and discuss their results to the others participants in the classroom. Computer programs are provided to the students who adapt those to determine inventory control parameters and to simulate inventory system performance. Case study and business game sessions give the participants a first hand, interactive experimental experience into the dynamics of inventory systems and real world problems. Guest lectures given by industry professionals supplement the theory parts and give the participants the opportunity to recognize problems, discover interesting challenges for choosing their thesis work and discuss with practitioners.