Course detail

Operational and System Analysis

FAST-NPA017Acad. year: 2026/2027

The course provides an overview of fundamental methods of operations research and systems analysis, with a focus on their application to problems in water management and civil engineering. It covers the formulation and analysis of decision-making and optimisation problems, linear and nonlinear programming, dynamic programming, multicriteria optimisation, graph theory and network analysis methods. The course also introduces the fundamentals of project management, risk analysis and selected computational intelligence methods, particularly artificial neural networks and genetic algorithms. Attention is paid to the practical application of individual methods and software tools in solving model problems.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Department

Institute of Municipal Water Management (VHO)

Entry knowledge

Knowledge of mathematics at the level of a bachelor's degree programme in Civil Engineering and basic user skills in Microsoft Excel.

Rules for evaluation and completion of the course

Conditions for Awarding the Course Credit

The conditions for awarding the course credit are:

  • compulsory attendance at practical classes,
  • submission of all required assignments,
  • correct completion of all required assignments; any deficiencies must be corrected in accordance with the instructor’s instructions.

One duly excused absence from practical classes may be approved by the instructor. Two or more absences are assessed and may be excused by the course guarantor. In justified cases, the course guarantor may specify an alternative way of fulfilling the attendance requirement.

Fulfilment of all the above conditions is required for the award of the course credit. Obtaining the course credit is a prerequisite for taking the examination.

Examination

The examination begins with a written test. To proceed with the examination, at least 50% of the available points must be achieved in the written test.

The written test result determines the subsequent course of the examination and provides the initial level for determining the final grade. If the written test result is 50–69%, a compulsory oral part of the examination follows. The oral part serves to verify the actual level of professional knowledge, understanding of relevant relationships and the ability to apply acquired knowledge.

Based on the result of the oral examination, the grade corresponding to the written test result may be improved by no more than one grade, remain unchanged, or be lowered.

The final grade is determined as follows:

  • 0–49%: the minimum required level for the written part has not been achieved; the final grade is F and the examination ends at this point.
  • 50–59%: a compulsory oral examination follows; depending on its result, the final grade may be D, E or F.
  • 60–69%: a compulsory oral examination follows; depending on its result, the final grade may be C, D, E or F.
  • 70–79%: the final grade is C without a compulsory oral examination.
  • 80–89%: the final grade is B without a compulsory oral examination.
  • 90–100%: the final grade is A without a compulsory oral examination.

Assessment of the Oral Examination

The oral examination normally includes questions from at least two different subject areas of the course and focuses in particular on assessing:

  • the correctness and scope of professional knowledge,
  • understanding of fundamental principles and their interrelationships,
  • the ability to explain the subject matter correctly using appropriate professional terminology,
  • the ability to apply acquired knowledge when solving a specific problem.

To improve the grade by one level, the oral examination must demonstrate knowledge, understanding of relevant relationships and the ability to apply acquired knowledge at a level clearly exceeding that indicated by the written test result.

To retain the grade corresponding to the written test result, the level of knowledge demonstrated during the oral examination must correspond to that level.

If only the minimum required level of knowledge is demonstrated during the oral examination, the final grade may be lower than the grade corresponding to the written test result. If the minimum required level of knowledge is not demonstrated during the oral examination, the final grade is F.

Aims

Upon successful completion of the course, students will acquire the knowledge, skills and competences required to formulate, solve and evaluate basic optimisation and decision-making problems, with a focus on their application in water management and civil engineering.

Knowledge

Upon successful completion of the course, students will:

  • know the basic principles of operations research, optimisation and the systems approach to solving technical problems,
  • know the principles of linear, nonlinear and dynamic programming,
  • understand the fundamentals of multicriteria optimisation and decision-making,
  • know the fundamentals of graph theory and network analysis methods,
  • be familiar with the basic principles of project management and risk analysis,
  • know the basic principles of selected computational intelligence methods, particularly artificial neural networks and genetic algorithms,
  • understand the possibilities and limitations of applying individual methods to problems in water management and civil engineering.

Skills

Upon successful completion of the course, students will be able to:

  • formulate a basic decision-making or optimisation problem and identify its main variables, objectives and constraints,
  • select an appropriate basic approach for solving linear, nonlinear and multicriteria optimisation problems,
  • solve basic optimisation problems using appropriate software tools, particularly Solver in Microsoft Excel,
  • apply basic principles of graph theory and network analysis to model technical problems,
  • solve basic project management tasks using appropriate software tools,
  • interpret and evaluate the results of optimisation, decision-making and risk analyses,
  • explain the principles and potential applications of artificial neural networks and genetic algorithms in solving technical problems.

Competences

Upon successful completion of the course, students will be able to:

  • independently transform a basic technical problem into a form suitable for analytical or optimisation-based solution,
  • select and professionally justify an appropriate solution method with regard to the nature of the problem and the available data,
  • critically assess the results of a model-based solution, including its assumptions and limitations,
  • apply operations research and systems analysis methods to problems in water management and civil engineering,
  • professionally interpret, present and justify the proposed solution approach and the results obtained.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme NPC-SIV Master's 1 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Syllabus

  • 1. Subject of operational and system analysis, basic terms and types of problems.
  • 2. Linear programming – Simplex method.
  • 3. Dual problem of linear programming, specific problems of linear programming.
  • 4. Transportation problem – solving by MODI method.
  • 5. Non-linear programming, method of objective function linearization.
  • 6. Non-linear programming – Lagrange method.
  • 7. Polyoptimal problems, pareto solving techniques.
  • 8. Combinatorial problems, bivalent programming.
  • 9. Graph theory, minimum graph frame and minimum graph trace.
  • 10. Network analysis – methods of project control.
  • 11. Dynamic programming.
  • 12. Neural networks, genetic algorithms.
  • 13. Risk analysis.

Exercise

39 hours, compulsory

Teacher / Lecturer

Syllabus

  • 1. Excel SOLVER.
  • 2. Linear programming – methods of graphical solution.
  • 3. Linear programming – Simplex method – Excel SOLVER.
  • 4. Dual problem of linear programming – Excel SOLVER.
  • 5. Distriubution problem – Excel SOLVER.
  • 6. Non-linear programming – Lagrange method.
  • 7. Non-linear programming – Lagrange method.
  • 8. Combinatorial methods – method Monte-Carlo.
  • 9. MS Project software tool.
  • 10. Graph theory – Critical Path Method.
  • 11. MS Project – project management.
  • 12. MS Project – project management.
  • 13. Credit.