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A Knee-Based EMO Algorithm with an Efficient Method to Update Mobile Reference Points

  • Yu SetoguchiEmail author
  • Kaname Narukawa
  • Hisao Ishibuchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9018)

Abstract

A number of evolutionary multi-objective optimization (EMO) algorithms have been proposed to search for non-dominated solutions around reference points that are usually assumed to be given by a decision maker (DM) based on his/her preference. However, setting the reference point needs a priori knowledge that the DM sometimes does not have. In order to obtain favorable solutions without a priori knowledge, “knee points” can be used. Some algorithms have already been proposed to obtain solutions around the knee points. TKR-NSGA-II is one of them. In this algorithm, the DM is supposed to specify the number of knee points as a parameter whereas such information is usually unknown. In this paper, we propose an EMO algorithm that does not require the DM to specify the number of knee points in advance. We demonstrate that the proposed method can efficiently find solutions around knee points.

Keywords

Knee point Preference Reference point Decision maker 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Yu Setoguchi
    • 1
    Email author
  • Kaname Narukawa
    • 2
  • Hisao Ishibuchi
    • 1
  1. 1.Department of Computer Science and Intelligent Systems, Graduate School of EngineeringOsaka Prefecture UniversitySakaiJapan
  2. 2.Honda Research Institute Europe GmbHOffenbach am MainGermany

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