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Regular version of the site
Master 2019/2020

Dynamic optimization for Business research

Area of studies: Management
When: 2 year, 1, 2 module
Mode of studies: Blended
Instructors: Igor Sloev
Master’s programme: Management and Analytics for Business
Language: English
ECTS credits: 3

Course Syllabus

Abstract

This course covers topics in dynamic optimization methods which might be relevant for applied business research: investment decisions, pricing etc. It discovers and explores cases both in discrete and in continuous time. The methodological approaches address methods in dynamic programming and optimal solutions across infinite/finite time horizons. The course illustrates how dynamic optimization is useful for business strategies development on a rigorous analytical base.
Learning Objectives

Learning Objectives

  • introduce students to the main types of optimization problems and approaches to their solution;
  • master the methods of solving optimization dynamic problems in discrete time
  • teach students to apply dynamic optimization methods to solve applied problems in management
Expected Learning Outcomes

Expected Learning Outcomes

  • to apply dynamic optimization techniques for different business problems
  • to construct Bellman equation and find close-form solution if possible
  • to differentiate dynamic optimisation methods
  • to distinguish situations where dynamic optimisation methods can be used
  • to estimate Bellman equation
Course Contents

Course Contents

  • Programming modelling for business solutions
  • Bellman equation for value and profit functions
  • SML and SMM for problems without close-form solutions
Assessment Elements

Assessment Elements

  • non-blocking Control work
  • non-blocking Problem-solving discussions
  • non-blocking Labs
  • non-blocking exam
Interim Assessment

Interim Assessment

  • Interim assessment (2 module)
    0.1 * Control work + 0.5 * exam + 0.3 * Labs + 0.1 * Problem-solving discussions
Bibliography

Bibliography

Recommended Core Bibliography

  • Blot, J., & Hayek, N. (2014). Infinite-Horizon Optimal Control in the Discrete-Time Framework. New York: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=662694

Recommended Additional Bibliography

  • Akram Chibani, Xavier Delorme, Alexandre Dolgui, & Henri Pierreval. (2018). Dynamic optimisation for highly agile supply chains in e-procurement context. International Journal of Production Research, (17), 5904. https://doi.org/10.1080/00207543.2018.1458164