Thesis topics


There are several thesis topics available for bachelor, master, and Ph.D. students. Below is some examples of the topics.

Thesis topics for motivated doctoral students:

  • Investigation of different hybridization techniques in evolutionary multi-objective optimization involving more than 3 objectives (Ph.D.)
  • Dynamic multi-objective optimization algorithms involving very large number of computationally expensive objectives (Ph.D.)
  • Enhanced constraint handling techniques for surrogate based evolutionary multi-objective optimization (Ph.D.)
  • Evaluating conflict between the objectives in multiobjective optimization (Bachelor/Master/Ph.D.)
  • Pascoletti-Serafini scalarization in multiobjective optimization (bachelor/Master/Ph.D.)

Thesis topics for motivated bachelor/master students:

  • Evaluating conflict between the objectives in multiobjective optimization (Bachelor/Master/Ph.D.)
  • Pascoletti-Serafini scalarization in multiobjective optimization (bachelor/Master/Ph.D.)
  • On using grid computing in optimization (Bachelor/Master)
  • LocalSolver (http://www.localsolver.com/) for mathematical optimization: Features and utilization possibilities (Bachelor/Master)
  • On capabilities of the PISA optimization platform (Bachelor/Master)
  • Optimization using Matlab (Bachelor/Master)
  • Multiobjective supply chain optimization (Bachelor/Master)
  • Experimental investigation of DAKOTA (http://dakota.sandia.gov/index.html) for large-scale optimization (Master)
  • Optimal forest management planning under uncertainty (Master). Joint work with the University of Helsinki
  • An experimental study of high performance evolutionary multi-objective optimization algorithms (Master)
  • Parallel implementation and analysis of NSGA-III algorithm for computationally expensive problems (Master)
  • Analysis of constraint handling techniques on NSGA-III algorithm (Master)
  • A parametric study on NSGA-III algorithm (Master)
  • Trade-off analysis approach for interactive nonlinear multiobjective optimization - challenges in implementation (Master)

Motivated students can send E-mails with CV and recommendation letters to Prof. Kaisa Miettinen kaisa.miettinen at jyu.fi.