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
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- Väitöskirjat [3599]
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A Performance Indicator for Interactive Evolutionary Multiobjective Optimization Methods
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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 ... -
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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 ... -
Potential of interactive multiobjective optimization in supporting the design of a groundwater biodenitrification process
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