Gurantor department | Department of Computer Science | Credits | 4 |

Subject guarantor | doc. Ing. Pavel Krömer, Ph.D. | Subject version guarantor | doc. Ing. Pavel Krömer, Ph.D. |

Study level | undergraduate or graduate | Requirement | Optional |

Year | 1 | Semester | summer |

Study language | English | ||

Year of introduction | 2015/2016 | Year of cancellation | |

Intended for the faculties | FEI | Intended for study types | Follow-up Master |

Instruction secured by | |||
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Login | Name | Tuitor | Teacher giving lectures |

KRO080 | doc. Ing. Pavel Krömer, Ph.D. |

Extent of instruction for forms of study | ||
---|---|---|

Form of study | Way of compl. | Extent |

Full-time | Credit and Examination | 2+2 |

Combined | Credit and Examination | 10+0 |

The aim of this course is to teach the basic deterministic and advanced stochastic methods for solving different complex combinatorial / discrete problems of an optimization nature. This course will also introduce different problems in transportation, assignment and scheduling, which are common and have a practical foundation.
Upon completion of the course, the students will be able to solve, (by making use of various methods) various tasks from the area of production control and planning, logistics, routing etc. The emphasis will be also on obtaining the practical experience with solving the tasks from this area.

Lectures

Tutorials

Operations research (OR) is a set of scientific disciplines focused on decision and optimization problems. Also known as management science or decision science, it involves the application of various mathematical methods and computer science in the design and optimization of systems and in the search for optimum decisions, especially regarding resource allocation.
The course introduces the fundamentals, basic principles, problems, and methods of operations research. It discusses the historical context, properties of solved problems, and the impact of operations research. Mathematical modelling of real-world problems as well as the task of parameter optimization is presented. Convex optimization, quadratic, and linear programming techniques and their applications are outlined. The lectures extend the simplex algorithm with the application of bound variables and revised simplex algorithm for faster execution. Multiobjective problems and methods in the context of linear programming are discussed on the example of the goal programming.

1. Taha Hamdy (2010) Operations Research: An Introduction (9th Edition). ISBN-13: 978-0132555937
2. Winston Wayne (2003) Operations Research: Applications and Algorithms. ISBN-13: 978-0534380588
3. Pinedo M. (2012) Scheduling: Theory, Algorithms, and Systems. Springer. ISBN-13: 978-1461419860

1. Marlow W. Mathematics for Operations Research. Dover Publications. ISBN-13: 978-0486677231

Conditions for granting the credit:
The tasks that form the program of exercises must be worked out.

Additional requirements are placed on the student.

Subject has no prerequisities.

Subject has no co-requisities.

Operations Research (OR) is a discipline of applying advanced analytical methods to help make better decisions. Also known as management science or decision science, it involves the application of information technology in designing systems to operate in the most effective way or deciding how to allocate scarce human resources, money, equipment, or facilities.
This course will address the three different aspects of OR, which are:
1. Simulation: the ability to try out approaches and test ideas for improvement
2. Optimisation: Narrowing choices to the very best when there are virtually innumerable feasible options and comparing them is difficult
3. Probability and Statistics: measure risk, mine data to find valuable connections and insights, test conclusions, and make reliable forecasts.
Lectures:
1. Linear programming formulation
2. Linear programming solution – graphical method
3. Linear programming solution – algebraic method
4. Simplex algorithm
5. Big-M Method
6. Two Phase Method
7. Simplex algorithm – Initialisation and Iteration
8. Simplex algorithm – Termination
9. Primal – Dual Relationship
10. Dual Simplex Algorithm
11. Introduction to Sensitivity Analysis
12. Transportation problem
13. Assignment problems
14. Hungarian Algorithm
Computer labs:
1. Bio-Inpired Algorithms
2. Programming Permutative Flowshop scheduling problem
3. Programming Flowshop with blocking scheduling problem
4. Programming Flowshop with no-wait scheduling problem
5. Programming Capacitated Vehicle Routing problem
6. Programming Traveling Salesman Problem
7. Programming Bin Packing Problem
8. Programming Quadratic Assignment Problem
9. Development of the Simplex Algorithm
10. Evaluation of Simplex algorithm on scheduling problems
11. Evaluation of Simplex algorithm on routing and assignment problems
12. Evaluation of Bio-Inspired algorithms on scheduling problems
13. Evaluation of Bio-Inspired algorithm on routing and assignment problems
14. Analysis of effective algorithms for different problems

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Credit and Examination | Credit and Examination | 100 (100) | 51 |

Credit | Credit | 45 | 20 |

Examination | Examination | 55 | 6 |

Show history

Academic year | Programme | Field of study | Spec. | Form | Study language | Tut. centre | Year | W | S | Type of duty | |
---|---|---|---|---|---|---|---|---|---|---|---|

2019/2020 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | English | Ostrava | 1 | Optional | study plan | |||

2019/2020 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | English | Ostrava | 1 | Optional | study plan | |||

2018/2019 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | English | Ostrava | 1 | Optional | study plan | |||

2018/2019 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | English | Ostrava | 1 | Optional | study plan | |||

2017/2018 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | English | Ostrava | 1 | Optional | study plan | |||

2017/2018 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | English | Ostrava | 1 | Optional | study plan | |||

2016/2017 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | English | Ostrava | 1 | Optional | study plan | |||

2016/2017 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | English | Ostrava | 1 | Optional | study plan | |||

2015/2016 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | P | English | Ostrava | 1 | Optional | study plan | |||

2015/2016 | (N2647) Information and Communication Technology | (2612T025) Computer Science and Technology | K | English | Ostrava | 1 | Optional | study plan |

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