Course detail

Operational and System Analysis

FAST-CP003Acad. year: 2018/2019

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.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

doc. Ing. Ladislav Tuhovčák, CSc.

Department

Institute of Municipal Water Management (VHO)

Learning outcomes of the course unit

The ability to define constraints and criteri functions for selected optimization tasks, handle simple mathematical methods of water optimization problems, handle the basics of MS Project software for project management, an overview of the possibilities of using neural networks, genetic algorithms and selected methods of risk analysis.

Prerequisites

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

Co-requisites

Not required

Planned learning activities and teaching methods

Presentation of the recommended computational procedures, examples of the method in watre management, processing of network graphs and Gannt diagrams of the structures for selected water management facility in MS Project.

Assesment methods and criteria linked to learning outcomes

Mandatory participation in seminars(only allowed two excused absence, submitting examples of exercises deadlines. Written and oral examination.

Course curriculum

1. Subject of operational and system analysis, basic terms and types of problems
2. Linear programming – methods of graphical solution, 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

Work placements

Not applicable.

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.

Specification of controlled education, way of implementation and compensation for absences

Extent and forms are specified by guarantor’s regulation updated for every academic year.

Recommended optional programme components

Study of selected foreign papers and other recommended references in the field of optimization tasks used in water management.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme N-P-E-SI (N) Master's

    branch V , 1. year of study, winter semester, compulsory

  • Programme N-P-C-SI (N) Master's

    branch V , 1. year of study, winter semester, compulsory

  • Programme N-K-C-SI (N) Master's

    branch V , 1. year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

doc. Ing. Ladislav Tuhovčák, CSc.

Syllabus

1. Subject of operational and system analysis, basic terms and types of problems
2. Linear programming – methods of graphical solution, 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

doc. Ing. Ladislav Tuhovčák, CSc.

Syllabus

1. Excel
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