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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 2023
Semester:	summer
E-Credits:	3
Hours per week, examination:	summer s.:2/0, Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech, English
Teaching methods:	full-time
Teaching methods:	full-time
Additional information:	https://kam.mff.cuni.cz/~hladik/VP/

Guarantor:	prof. Mgr. Milan Hladík, Ph.D.
Class:	Informatika Mgr. - Diskrétní modely a algoritmy
Classification:	Informatics > Optimalization

Opinion survey results Examination dates SS schedule Noticeboard

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.