Interactivized : Visual Interaction for Better Decisions with Interactive Multiobjective Optimization
Hakanen, J., Radoš, S., Misitano, G., Saini, B. S., Miettinen, K., & Matković, K. (2022). Interactivized : Visual Interaction for Better Decisions with Interactive Multiobjective Optimization. IEEE Access, 10, 33661-33678. https://doi.org/10.1109/access.2022.3161465
Julkaistu sarjassa
IEEE AccessTekijät
Päivämäärä
2022Oppiaine
TietotekniikkaLaskennallinen tiedeMultiobjective Optimization GroupPäätöksen teko monitavoitteisestiMathematical Information TechnologyComputational ScienceMultiobjective Optimization GroupDecision analytics utilizing causal models and multiobjective optimizationTekijänoikeudet
© Authors, 2022
In today’s data-driven world, decision makers are facing many conflicting objectives. Since there is usually no solution that optimizes all objectives simultaneously, the aim is to identify a solution with acceptable trade-offs. Interactive multiobjective optimization methods are iterative processes in which a human decision maker repeatedly provides one’s preferences to request computing new solutions and compares them. With these methods, the decision maker can learn about the problem and its limitations. However, advanced optimization software usually offer simple visualization tools that can be significantly improved. On the other hand, current approaches for multiobjective optimization from the visualization community provide superior visualization tools but lack advanced optimization. In this paper, we introduce a new term, interactivize, for integrating interactive multiobjective optimization and interactive visualization and present an interactivized approach supporting decision makers in visually steering interactive multiobjective optimization methods. We integrate state-of-the-art interactive visualization with the process of interactive multiobjective optimization in a visual analytics solution that significantly improves the analysis workflow of decision makers, like comparing selected solutions and specifying new preferences during the iterative solution process. To realize the new interactivized approach, we combine a coordinated multiple views system with DESDEO, an open-source software framework for interactive multiobjective optimization. We demonstrate our interactivized approach on a river pollution problem.
...
Julkaisija
IEEEISSN Hae Julkaisufoorumista
2169-3536Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/117423579
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Rahoittaja(t)
Suomen AkatemiaRahoitusohjelmat(t)
Akatemiahanke, SA; Profilointi, SALisätietoja rahoituksesta
This work was partly supported by the Academy of Finland, grant numbers 311877 and 322221, and by the COMET program of the FFG (879730).Lisenssi
Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
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 ... -
Towards explainable interactive multiobjective optimization : R-XIMO
Misitano, Giovanni; Afsar, Bekir; Lárraga, Giomara; Miettinen, Kaisa (Springer Science and Business Media LLC, 2022)In interactive multiobjective optimization methods, the preferences of a decision maker are incorporated in a solution process to find solutions of interest for problems with multiple conflicting objectives. Since multiple ... -
Desirable properties of performance indicators for assessing interactive evolutionary multiobjective optimization methods
Aghaei Pour, Pouya; Bandaru, Sunith; Afsar, Bekir; Miettinen, Kaisa (ACM, 2022)Interactive methods support decision makers in finding the most preferred solution in multiobjective optimization problems. They iteratively incorporate the decision maker's preference information to find the best balance ... -
Integration of lot sizing and safety strategy placement using interactive multiobjective optimization
Kania, Adhe; Sipilä, Juha; Misitano, Giovanni; Miettinen, Kaisa; Lehtmäki, Jussi (Elsevier, 2022)We address challenges of unpredicted demand and propose a multiobjective optimization model to integrate a lot sizing problem with safety strategy placement and optimize conflicting objectives simultaneously. The novel ... -
Interactive data-driven multiobjective optimization of metallurgical properties of microalloyed steels using the DESDEO framework
Saini, Bhupinder Singh; Chakrabarti, Debalay; Chakraborti, Nirupam; Shavazipour, Babooshka; Miettinen, Kaisa (Elsevier BV, 2023)Solving real-life data-driven multiobjective optimization problems involves many complicated challenges. These challenges include preprocessing the data, modelling the objective functions, getting a meaningful formulation ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.