Angle-based preference models in multi-objective optimization

Marlon Braun, Pradyumn Shukla, Hartmut Schmeck

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Solutions that provide a balance between different objective values in multi-objective optimization can be identified by assessing the curvature of the Pareto front. We analyze how methods based on angles have been utilized in the past for this task and propose a new angle-based measure—angle utility—that ranks points of the Pareto front irrespective of its shape or the number of objectives. An algorithm for finding angle utility optima is presented and a computational study shows that this algorithm is successful in identifying angle utility optima.

Original languageEnglish
Title of host publicationEvolutionary Multi-Criterion Optimization - 9th International Conference, EMO 2017, Proceedings
EditorsOliver Schütze, Gunter Rudolph, Kathrin Klamroth, Yaochu Jin, Heike Trautmann, Christian Grimme, Margaret Wiecek
PublisherSpringer-Verlag Italia
Number of pages15
ISBN (Print)9783319541563
Publication statusPublished - 19 Feb 2017
Event9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017 - Munster, Germany
Duration: 19 Mar 201722 Mar 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10173 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2017


  • Angle utility
  • Evolutionary algorithm
  • Multi-objective optimization
  • Preference modeling
  • Scalarization


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