On scalarizing functions in multiobjective optimization

By Kaisa Miettinen, M. Mäkelä. OR Spectr., 2002

309 citations recorded by the source corpus.

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The effect of normalization norms in multiple attribute decision making models: a case study in gear material selection (2005, background): “For engineering designs, material properties can be classified as shown in Table 1 ( Mangono 1999 ).”
Multi-objective reinforcement learning using sets of pareto dominating policies (2014, methodology): “The simplest way is to use a scalarization function (Miettinen and Mäkelä, 2002) which transforms the multi-objective problem into a standard single-objective problem.”
NeurAll: Towards a Unified Visual Perception Model for Automated Driving (2019, methodology): “For scalarization of the three loss functions, we use the standard sum of the losses as a baseline and improve it by using product of losses inspired by its use in game theory [46].”
NeurAll: Towards a Unified Model for Visual Perception in Automated Driving (2019, methodology): “For scalarization of the three loss functions, we use the standard sum of the losses as a baseline and improve it by using product of losses inspired by its use in game theory [46].”