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Regular version of the site
Master 2021/2022

Supply Chain Analytics

Type: Elective course (Strategic Management of Logistics and Supply Chains in the Digital Economy)
Area of studies: Management
When: 2 year, 2 module
Mode of studies: distance learning
Online hours: 2
Open to: students of all HSE University campuses
Instructors: Vadim Korepin, Gleb Zakhodiakin
Master’s programme: Стратегическое управление логистикой и цепями поставок в цифровой экономике
Language: English
ECTS credits: 4
Contact hours: 22

Course Syllabus

Abstract

This course is intended for Logistics and Supply Chain Management majors at Master of Science level who want to learn modeling-based methods and software for supply chain design and management. The prerequisite for this course is a deep understanding of key concepts in supply chain management. The participants will also deal with mathematical and simulation models of supply chains. The specialized software for building such models is used in the course. The course materials provide all necessary mathematical and simulation methods and tools to understand the concepts being studied. After a brief review of the supply chain concept and key elements, the course introduces a mathematical programming-based approach to supply chain modeling and design. Then we will be building supply chain network models for distribution and manufacturing companies using specialized software. The concepts of multi-objective analysis will be introduced. The course also introduces the concept of uncertainty and explains its influence on making model-based decisions in supply chain management. We will use the simulation-based approach and software to study the effects of uncertainty on inventory management and supply chain reliability. An introduction to the modeling approach and the basics of mathematical programming, probability, statistics and data analysis are provided via a blended MOOC - Supply Chain Analytics from MIT (https://www.edx.org/course/supply-chain-analytics-0).
Learning Objectives

Learning Objectives

  • To understand how modeling-based methods and tools are supporting logistics and supply chain management decisions
Expected Learning Outcomes

Expected Learning Outcomes

  • Can collect and interpret supply chain statistics in Anylogistix
  • Can create supply chain models using special software
  • Can describe a supply chain in terms of structural and functional attributes
  • Can explain in own words the difference between simulation and analytical supply chain models
  • Can implement a supply chain model in Anylogistix
  • Can optimize inventory policies in Anylogistix software
  • Can reproduce and interpret the mathematical formulation for basic supply chain elements (plants, warehouses, transportation routes) using MILP
Course Contents

Course Contents

  • Analytical tasks in supply chain management
  • Mixed-integer linear programming for supply chain design and planning
  • Simulation for supply chain design and planning
Assessment Elements

Assessment Elements

  • non-blocking Participation
  • non-blocking Presentation
  • blocking Final Project
Interim Assessment

Interim Assessment

  • 2021/2022 2nd module
    Расчет производится по принципам, установленным авторами курса, в электронном виде на сайте дисциплины https://www.edx.org/course/supply-chain-analytics-0
Bibliography

Bibliography

Recommended Core Bibliography

  • Modeling the supply chain, Shapiro, J. F., 2001
  • Operations management : sustainability and supply chain management, Heizer, J., 2014

Recommended Additional Bibliography

  • Advanced planning in supply chains : illustrating the concepts using an SAP APO case study, Stadtler, H., 2012
  • Logistics and supply chain management. Creating value-adding networks, Christopher M., 2005

Authors

  • KOREPIN VADIM NIKOLAEVICH
  • ZAKHODYAKIN GLEB VIKTOROVICH