Optimization modelling in public sector

Optimization modelling in public sector

  • Study programme and level:The joint doctoral study programme Governance and Economics in the Public Sector (third cycle)
  • 1st year
  • 5 ECTS
  • Course type: Elective course
  • Lectures: 20
  • Seminar: 20
  • Other forms of study: 20
  • Individual work:  90
  • Lecturer: Jože Benčina, PhD

1. Objectives and competences

Students:

  • independently analyses public sector organisations performance and appoints questions and issues of public sector optimisation problems,  
  • identify settings in which models can be used effectively and apply modelling concepts in practical situations,
  • makes critical reflexion of the results and detects opportunities to enhance optimisation model and improve public sector performance.

 Student is qualified:

  • to translate descriptions of optimisation problems into formal models, and investigate those models in an organized fashion,
  • for comparative analysis and decision making about which optimisation method is the most suitable for particular formal optimisation model,
  • to build new knowledge by inductive reasoning on phenomena characteristics with the help of suitable optimisation models,
  • for deductive implementation of models, critical evaluation of their practical usefulness and use of the research results to enhance the optimisation models.

2. Content (Syllabus outline)

This course builds on the optimization coverage in the core and provides the student with advanced modelling and optimization tools that can be useful in public sector. We begin by reviewing the formulation and interpretation of optimisation problems in public sector. The course provides an overview of the major types of optimisation tools including Data Envelopment Analysis (DEA), a sophisticated linear programming approach to evaluating the efficiency of similar businesses or operating units. We discuss the use of fuzzy logic in optimisation problems. Each student will analyse chosen optimisation problem and design suitable optimisation solutions. The results will be reported in a research paper.
The course topics are:

  • Modelling and optimisation concept
  • Core optimisation problems, the definition of the optimisation problem in public sector
  • An overview of the major types of optimisation models and their applications in public sector
  • Four steps of an optimisation model application procedure, problem analysis, plan, model design, solution
  • Optimisation modelling software tools
  • Fuzzy logic essentials
  • Classical optimisation and heuristic techniques
  • Data envelopment analysis
  • Fuzzy optimisation models
  • Interpretation of the optimisation modelling results

3.  Readings

  •  Chong, Edwin Kah Pin , Żak, Stanislaw H. (2008): An introduction to optimization, 3rd ed. Hoboken (New Jersey) : Wiley-Interscience, 584 str.
  • Sarker, Ruhul A., Newton, Charles Sinclair (2008): Optimization modeling : a practical approach. Boca Raton, London, New York : CRC Press, 469 str.
  • Cooper, William Wager, Seiford, Lawrence M., (2007): Data envelopment analysis : a comprehensive text with models, applications, references and DEA-solver software, 2nd ed., New York : Springer, 490 str.
  • Zimmermann Hans Juergen: Fuzzy Set Theory and Its Applications. 4th ed. Dodrecht: Kluver Academic Publishers, 2001. 514 str.
  • Relevant literature, articles to be arranged with the instructor.

4. Intended learning outcomes

Students will understand the role and opportunities of optimisation modelling as the crucial leverage of public sector operations enhancement; act as innovative discoverer of opportunities for use of optimisation models in public sector; be able  to plan construction and modulation of optimisation models in public sector; be able to implement optimisation models in public sector operations and assure their long lasting influence on public sector performance; understand the importance of critical reflection of theoretical and practical results of optimisation modelling.

5. Learning and teaching methods

  • Lecture.
  • Research.
  • Project work.
  • Seminar paper.

6. Assessment

Research report, writing and presentation - 80%
Oral exam - 20%