MathMods :: Joint MSc

Numerical optimization

Additional Info

  • ECTS credits: 6
  • Semester: 2
  • University: Vienna University of Technology
  • Objectives:


    Learn the basic concepts and methods of unconstrained and constrained optimization.

  • Topics:


    Unconstrained optimisation: gradient methods, classical Newton method, quasi-Newton method (e.g. BFGS method). Constrained optimisation: trust region methods, linear programming (simplex method, interior point method), quadratic programming (inner point method, active sets method), sequential quadratic programming.

Read 2109 times Last modified on Tuesday, 20 February 2018 16:48

Connect with us

Our partners' addresses

University of L'Aquila, Italy (UAQ)

Department of Information Engineering, Computer Science and Mathematics, via Vetoio (Coppito), 1 – 67100 L’Aquila (Italy)

University of Hamburg , Germany (UHH)

Department of Mathematics
Bundesstr. 55
20146 Hamburg - Germany

University of Côte d'Azur, Nice - France (UCA)

Laboratoire J.A.Dieudonné
Parc Valrose, France-06108 NICE Cedex 2

Vienna Univ. of Technology, Austria (TUW)

Technische Universität Wien
Institute of Analysis & Scientific Computing
Wiedner Hauptstr. 8, 1040 Vienna - Austria

This web-site reflects the views only of the author, and the EU Commission cannot be held responsible for any use which may be made of the information contained therein.