2021
DOI: 10.1007/978-3-030-72062-9_49
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An Artificial Decision Maker for Comparing Reference Point Based Interactive Evolutionary Multiobjective Optimization Methods

Abstract: Comparing interactive evolutionary multiobjective optimization methods is controversial. The main difficulties come from features inherent to interactive solution processes involving real decision makers. The human can be replaced by an artificial decision maker (ADM) to evaluate methods quantitatively. We propose a new ADM to compare reference point based interactive evolutionary methods, where reference points are generated in different ways for the different phases of the solution process. In the learning p… Show more

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Cited by 10 publications
(22 citation statements)
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“…To the best of our knowledge, there are only a few ADMs to compare interactive methods: [1,3,13,24]. The one suggested in [13] simulates the learning of a DM by progressively narrowing the angle of a cone, which is defined based on a pre-defined MPS.…”
Section: Introductionmentioning
confidence: 99%
“…To the best of our knowledge, there are only a few ADMs to compare interactive methods: [1,3,13,24]. The one suggested in [13] simulates the learning of a DM by progressively narrowing the angle of a cone, which is defined based on a pre-defined MPS.…”
Section: Introductionmentioning
confidence: 99%
“…In those experiments, one or few test runs for each studied method were performed with multiple (usually dozens of) participants. Comprehensive reviews of such studies can be found in [Afsar et al, 2021b], [Olson, 1992].…”
mentioning
confidence: 99%
“…[Barba-González et al, 2018] generate reference points based on particle swarm optimization. In [Afsar et al, 2021a], an artificial DM was proposed for simultaneous comparison of several interactive reference point based evolutionary multiobjective optimization methods. Different mechanisms were proposed for the learning and the decision phases to generate reference points.…”
mentioning
confidence: 99%
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