Objective reduction in multiobjective optimization
Tämän tutkielman tavoitteena on tarkastella menetelmiä, jotka pyrkivät ratkaisemaan ongelmia, jotka ilmenevät monitavoiteoptimointitehtävissä tavoitteiden määrän kasvaessa suureksi. Työssä esitellään useita menetelmiä kattaen erilaisia oletuksia optimointitehtävän luonteelta, kuten esimerkiksi lineaaristen tai konveksien tehtävien tapaukset. Lisäksi kommentoidaan menetelmien vahvuuksia ja heikkouksia. Yksi menetelmistä otetaan käytännönläheisempään tarkasteluun toteuttamalla siihen liittyvä abstrakti algoritmi Python-koodina ja tarkastelemalla algoritmin käyttäytymistä esimerkkien avulla. Lisäksi esitetään muutamia tapoja luokitella monitavoiteoptimointitehtävien tavoitteiden vähentämisen menetelmiä. The aim of this thesis is to study methods that have been created to avoid some of the problems related to solving multiobjective optimization problems with a large number of objectives. Multiple methods are presented covering various assumptions on the optimization problem, such as linearity or convexity, and the strengths and weaknesses of the methods are discussed. One of the methods is looked at in a more practical fashion, by presenting a Python code implementation of the abstract algorithm of the method in question and studying its behavior for some examples. Additionally, some criteria for classifying methods of objective reduction in multiobjective optimization are defined.
Metadata
Show full item recordCollections
- Pro gradu -tutkielmat [29626]
Related items
Showing items with similar title or keywords.
-
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 ... -
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 ... -
A Visualization Technique for Accessing Solution Pool in Interactive Methods of Multiobjective Optimization
Filatovas, Ernestas; Podkopaev, Dmitry; Kurasova, Olga (Universitatea Agora, 2015)Interactive methods of multiobjective optimization repetitively derive Pareto optimal solutions based on decision maker's preference information and present the obtained solutions for his/her consideration. Some interactive ... -
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 ... -
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 ...