Quantitative Methods of Decision Making

Course Overview

The course is designed for students who want to get acquainted with quantitative tools suitable for supporting decision-making occurring in business, economics, and finance. The main goal of the course is to show how to model real decision-making problems and to present methods of their solving. The secondary goal is to familiarize students with the use of MS Excel and its add-in Solver for solving optimization problems. Participants will be introduced to common application areas of Operations Research/ Management Science (OR-MS) and necessary solution procedures (simplex method, MODI, Hungarian method, CPM, and others). The course is ended by a team project. Team members should use skills gained in the course to build mathematical models for given case studies and employ the procedures mentioned above to solve arising decision problems.

Learning Outcomes

After completing the course, students will be able to:

  • build optimization models for decision problems that occur in management, economics, and finance.
  • choose suitable methods to solve optimization problems representing decision-making situations.
  • find the solution using software (Solver, MS Excel)
  • interpret and validate the results

Course Content

  • Linear programming and its applications
  • Sensitivity analysis
  • Production management problems
  • Transportation problems
  • Assignment problems
  • Integer programming
  • Network optimization (and Critical Path Method for project management)
  • Multi-criteria decision analysis, Portfolio optimization
  • Multi-criteria and goal programming
  • Data envelopment analysis for efficiency evaluation

Instructional Method

The classes include both theoretical training and problem-solving sessions. Students will discuss the solutions of case studies. Advanced problems will be solved in the form of team projects.

Required Course Materials

Students will be provided with all course materials including training problems for the seminars (assignments, data, spreadsheets), lecture slides, and other documents providing theoretical background. Technical equipment requirements: computers with MS Excel.

Assessment

  • Team project: 60%
  • Class activities 20%
  • Final test 20%