Schmitt, Thomas ; Hoffmann, Matthias ; Rodemann, Tobias ; Adamy, Jürgen (2022)
Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control.
In: Inventions, 7 (3)
doi: 10.3390/inventions7030046
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
We present a new two-step approach for automatized a posteriori decision making in multi-objective optimization problems, i.e., selecting a solution from the Pareto front. In the first step, a knee region is determined based on the normalized Euclidean distance from a hyperplane defined by the furthest Pareto solution and the negative unit vector. The size of the knee region depends on the Pareto front’s shape and a design parameter. In the second step, preferences for all objectives formulated by the decision maker, e.g., 50–20–30 for a 3D problem, are translated into a hyperplane which is then used to choose a final solution from the knee region. This way, the decision maker’s preference can be incorporated, while its influence depends on the Pareto front’s shape and a design parameter, at the same time favorizing knee points if they exist. The proposed approach is applied in simulation for the multi-objective model predictive control (MPC) of the two-dimensional rocket car example and the energy management system of a building.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Schmitt, Thomas ; Hoffmann, Matthias ; Rodemann, Tobias ; Adamy, Jürgen |
| Art des Eintrags: | Bibliographie |
| Titel: | Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Inventions |
| Jahrgang/Volume einer Zeitschrift: | 7 |
| (Heft-)Nummer: | 3 |
| Kollation: | 25 Seiten |
| DOI: | 10.3390/inventions7030046 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | We present a new two-step approach for automatized a posteriori decision making in multi-objective optimization problems, i.e., selecting a solution from the Pareto front. In the first step, a knee region is determined based on the normalized Euclidean distance from a hyperplane defined by the furthest Pareto solution and the negative unit vector. The size of the knee region depends on the Pareto front’s shape and a design parameter. In the second step, preferences for all objectives formulated by the decision maker, e.g., 50–20–30 for a 3D problem, are translated into a hyperplane which is then used to choose a final solution from the knee region. This way, the decision maker’s preference can be incorporated, while its influence depends on the Pareto front’s shape and a design parameter, at the same time favorizing knee points if they exist. The proposed approach is applied in simulation for the multi-objective model predictive control (MPC) of the two-dimensional rocket car example and the energy management system of a building. |
| Freie Schlagworte: | energy management system (EMS), MPC, normal boundary intersection (NBI), Pareto optimization, knee region, PARODIS |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungsmethoden und Robotik (ab 01.08.2022 umbenannt in Regelungsmethoden und Intelligente Systeme) |
| Hinterlegungsdatum: | 06 Dez 2023 09:34 |
| Letzte Änderung: | 06 Dez 2023 09:34 |
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| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
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Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control. (deposited 11 Jul 2022 13:30)
- Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control. (deposited 06 Dez 2023 09:34) [Gegenwärtig angezeigt]
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