Evolutionaariset monitavoiteoptimointialgoritmit
Tässä tutkielmassa selvitetään evolutionaaristen monitavoiteoptimointialgoritmien (MOEA) toimintaa. Tutkielmassa käydään evolutionaaristen menetelmien lisäksi läpi monitavoiteoptimointia. MOEA:ia kuvaillaan yleisellä tasolla, ja esitellään joitain tunnettuja algoritmeja pyrkien antamaan mahdollisimman kattavan kokonaisukuvan algoritmeista. Tutkielmassa vertaillaan myös algoritmeja toisiinsa ja tutkitaan niiden tehokkuutta. Goal of this thesis is to study evolutionary multiobjective optimization algorithms (MOEA). Multiobjective optimization is also presented. MOEAs are examined on abstract level and known algorithms are presented to give a comprehensive view of the algorithms. Algoritms are also compared to each other and their efficiency is explored.
Asiasanat
Metadata
Näytä kaikki kuvailutiedotKokoelmat
- Kandidaatintutkielmat [5362]
Lisenssi
Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
Multi-scenario multi-objective robust optimization under deep uncertainty : A posteriori approach
Shavazipour, Babooshka; Kwakkel, Jan H.; Miettinen, Kaisa (Elsevier BV, 2021)This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution ... -
LR-NIMBUS : an interactive algorithm for uncertain multiobjective optimization with lightly robust efficient solutions
Koushki, Javad; Miettinen, Kaisa; Soleimani-damaneh, Majid (Springer Science and Business Media LLC, 2022)In this paper, we develop an interactive algorithm to support a decision maker to find a most preferred lightly robust efficient solution when solving uncertain multiobjective optimization problems. It extends the interactive ... -
A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods
Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Emmerich, Michael; Miettinen, Kaisa (IEEE, 2024)In recent years, interactive evolutionary multiobjective optimization methods have been getting more and more attention. In these methods, a decision maker, who is a domain expert, is iteratively involved in the solution ... -
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 ... -
Handling simulation failures of a computationally expensive multiobjective optimization problem in pump design
Mazumdar, Atanu; Burkotová, Jana; Krátký, Tomáš; Chugh, Tinkle; Miettinen, Kaisa (Elsevier, 2024)Solving real-world optimization problems in engineering and design involves various practical challenges. They include simultaneously optimizing multiple conflicting objective functions that may involve computationally ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.