Showing items with similar title or keywords.

• Handling expensive multiobjective optimization problems with evolutionary algorithms 

  Chugh, Tinkle (University of Jyväskylä, 2017)

  Multiobjective optimization problems (MOPs) with a large number of conflicting objectives are often encountered in industry. Moreover, these problem typically involve expensive evaluations (e.g. time consuming simulations ...

• A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms 

  Chugh, Tinkle; Sindhya, Karthik; Hakanen, Jussi; Miettinen, Kaisa (Springer, 2019)

  Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, ...

• On approaches for solving computationally expensive multiobjective optimization problems 

  Tabatabaei, Seyed Mohammad Mehdi (University of Jyväskylä, 2016)

  In this thesis, we consider solving computationally expensive multiobjective optimization problems that take into account the preferences of a decision maker (DM). The aim is to support the DM in identifying the most ...

• On solving computationally expensive multiobjective optimization problems with interactive methods 

  Ojalehto, Vesa (University of Jyväskylä, 2014)

• DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization 

  Misitano, Giovanni; Saini, Bhupinder Singh; Afsar, Bekir; Shavazipour, Babooshka; Miettinen Kaisa (Institute of Electrical and Electronics Engineers (IEEE), 2021)

  Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the ...