Course Details

Operational and System Analysis

Academic Year 2024/25

NPA017 course is part of 1 study plan

​ NPC-SIV Winter Semester 1st year

The subject provide the basic overview of the terminology of system analysis and basic types of optimisation tasks including the most often used methods of operation research and its implementation in water management as linear programming, non-linear programming, dynamic programming, multi criteria optimistion, graph theory, network analysis methods, project management, arificial neural networks, genetic algorithm and risk analysis.

Credits

6 credits

Language of instruction

Czech

Semester

winter

Course Guarantor

doc. Ing. Jaroslav Raclavský, Ph.D.

Institute

Institute of Municipal Water Management

Forms and criteria of assessment

course-unit credit and examination

Entry Knowledge

Mathematics in scope of bachelor study program Civil Engineering, the basic knowledge of the Excel software tool.

Aims

Get the basic knowledge of operation reserach methods which are used in water management as a linear and non-linear programming, graph theory, multicriteria optimisation methods, Artificial Neural Networks, Genetic Algoritm. Handle the fundamental solution of optimization problems using the module SOLVER (Excel) and project management with MS Project tool.
The student manages the basic knowledge of linear and non-linear programming, graph theory, multicriteria optimisation methods, project management, Artificial Neural network and Genetic algoritm. Get the basic skill with using the software tools Excel-Solver and MS Project.

Offered to foreign students

Not to offer

Course on BUT site

https://www.vut.cz/en/students/courses/detail/281811

Lecture

13 weeks, 2 hours/week, elective

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

13 weeks, 3 hours/week, compulsory

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.