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Course, academic year 2022/2023
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Multiobjective Optimisation - NOPT017
Title: Vícekriteriální optimalizace
Guaranteed by: Department of Applied Mathematics (32-KAM)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: summer
E-Credits: 3
Hours per week, examination: summer s.:2/0, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: not taught
Language: Czech, English
Teaching methods: full-time
Additional information:
Guarantor: prof. Mgr. Milan Hladík, Ph.D.
Class: Informatika Mgr. - Diskrétní modely a algoritmy
Classification: Informatics > Optimalization
Annotation -
Last update: prof. Mgr. Milan Hladík, Ph.D. (07.04.2016)
The lecture studies decision situations, when more critria are involved. We show how to handle such optimization problems. Remark: The course can be tought once in two years.
Aim of the course -
Last update: prof. Mgr. Milan Hladík, Ph.D. (06.04.2016)

Students will learn not only the classical results in multiobjective programming, but also the current trends. Absolvents should be able to apply their knowledge in practice and also do the reserach in this field.

Literature -
Last update: prof. Mgr. Milan Hladík, Ph.D. (06.04.2016)

[1] M. Ehrgott. Multicriteria Optimization. 2nd ed. Springer, Berlin, 2005.

[2] L. Grygarová. Základy vícekriteriálního programování. UK, Praha, 1996.

Requirements to the exam - Czech
Last update: prof. Mgr. Milan Hladík, Ph.D. (14.02.2018)

Zkouška je ústní a požadavky odpovídají sylabu předmětu v rozsahu, který byl presentován na přednášce.

Syllabus -
Last update: prof. Mgr. Milan Hladík, Ph.D. (06.04.2016)
  • Eficient (Pareto-optimal) solutions
  • Skalarization and relation to efficient solutions
  • Special sub-classes: multiobjective convex and linear programming
  • Various approaches to solve the problem
  • Combinatorial multiobjective optimization (shortest path, minimum spanning tree)
  • Multicriteria decision making (DEA, AHP)

It is assumed that the students have a basic knowledge of optimization, in particular linear programming.

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