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Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control

Schmitt, Thomas ; Hoffmann, Matthias ; Rodemann, Tobias ; Adamy, Jürgen (2022):
Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control. (Publisher's Version)
In: Inventions, 7 (3), MDPI, e-ISSN 2411-5134,
DOI: 10.26083/tuprints-00021629,
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Item Type: Article
Origin: Secondary publication DeepGreen
Status: Publisher's Version
Title: Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control
Language: English
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.

Journal or Publication Title: Inventions
Volume of the journal: 7
Issue Number: 3
Place of Publication: Darmstadt
Publisher: MDPI
Collation: 25 Seiten
Uncontrolled Keywords: energy management system (EMS), MPC, normal boundary intersection (NBI), Pareto optimization, knee region, PARODIS
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics (from 01.08.2022 renamed Control Methods and Intelligent Systems)
Date Deposited: 11 Jul 2022 13:30
Last Modified: 06 Sep 2022 09:46
DOI: 10.26083/tuprints-00021629
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-216295
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/21629
PPN: 498913090
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