Interactive methods for multiobjective robust optimization
Julkaistu sarjassa
JYU dissertationsTekijät
Päivämäärä
2018Oppiaine
TietotekniikkaTekijänoikeudet
© The Author & University of Jyväskylä
Julkaisija
Jyväskylän yliopistoISBN
978-951-39-7549-4ISSN Hae Julkaisufoorumista
2489-9003Julkaisuun sisältyy osajulkaisuja
- Artikkeli I: Zhou-Kangas, Y., Miettinen, K., & Sindhya, K. (2019). Solving multiobjective optimization problems with decision uncertainty : an interactive approach. Journal of Business Economics, 89 (1), 25-51. DOI: 10.1007/s11573-018-0900-1
- Artikkeli II: Zhou-Kangas, Y., Miettinen, K., & Sindhya, K. (2018). Interactive Multiobjective Robust Optimization with NIMBUS. In M. Baum, G. Brenner, J. Grabowski, T. Hanschke, S. Hartmann, & A. Schöbel (Eds.), Simulation Science : First International Workshop, SimScience 2017, Göttingen, Germany, April 27–28, 2017, Revised Selected Papers (pp. 60-76). Cham: Springer. DOI: 10.1007/978-3-319-96271-9_4
- Artikkeli III: Zhou-Kangas, Y., & Miettinen, K. (2018). A Simple Indicator Based Evolutionary Algorithm for Set-Based Minmax Robustness. In A. Auger, C. M. Fonseca, N. Lourenço, P. Machado, L. Paquete, & D. Whitley (Eds.), Parallel Problem Solving from Nature - PPSN XV : 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part 1 (pp. 287-297). Cham: Springer. DOI: 10.1007/978-3-319-99253-2_23
- Artikkeli IV: Yue Zhou-Kangas and Anita Schöbel. The Price of Multiobjective Robustness: Analyzing Solution Sets to Uncertain Multiobjective Optimization Problems. Submitted manuscript
- Artikkeli V: Zhou-Kangas, Y., & Miettinen, K. (2019). Decision making in multiobjective optimization problems under uncertainty : balancing between robustness and quality. OR Spektrum, 41 (2), 391-413. DOI: 10.1007/s00291-018-0540-4
Asiasanat
Metadata
Näytä kaikki kuvailutiedotKokoelmat
- JYU Dissertations [852]
- Väitöskirjat [3568]
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 ... -
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 ... -
Interactive Multiobjective Robust Optimization with NIMBUS
Zhou-Kangas, Yue; Miettinen, Kaisa; Sindhya, Karthik (Springer, 2018)In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty ... -
Decision making in multiobjective optimization problems under uncertainty : balancing between robustness and quality
Zhou-Kangas, Yue; Miettinen, Kaisa (Springer, 2019)As an emerging research field, multiobjective robust optimization employs minmax robustness as the most commonly used concept. Light robustness is a concept in which a parameter, tolerable degradations, can be used to ... -
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 ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.