460-4121/02 – Operational Research I (OV I)

Gurantor departmentDepartment of Computer ScienceCredits4
Subject guarantordoc. Ing. Pavel Krömer, Ph.D.Subject version guarantordoc. Ing. Pavel Krömer, Ph.D.
Study levelundergraduate or graduateRequirementOptional
Year1Semestersummer
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesFEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
KRO080 doc. Ing. Pavel Krömer, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Combined Credit and Examination 10+0

Subject aims expressed by acquired skills and competences

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.

Teaching methods

Lectures
Tutorials

Summary

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.

Compulsory literature:

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

Recommended literature:

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

Way of continuous check of knowledge in the course of semester

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

E-learning

Další požadavky na studenta

Additional requirements are placed on the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

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

Conditions for subject completion

Combined form (validity from: 2015/2016 Winter semester)
Task nameType of taskMax. 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
Mandatory attendence parzicipation:

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Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType 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

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner