Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031)

Authors Carlos M. Fonseca, Kathrin Klamroth, Günter Rudolph, Margaret M. Wiecek and all authors of the abstracts in this report

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Author Details

Carlos M. Fonseca
  • University of Coimbra, PT
Kathrin Klamroth
  • Universität Wuppertal, DE
Günter Rudolph
  • TU Dortmund, DE
Margaret M. Wiecek
  • Clemson University, US
and all authors of the abstracts in this report

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Carlos M. Fonseca, Kathrin Klamroth, Günter Rudolph, and Margaret M. Wiecek. Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031). In Dagstuhl Reports, Volume 10, Issue 1, pp. 52-129, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


The Dagstuhl Seminar 20031 Scalability in Multiobjective Optimization carried on a series of six previous Dagstuhl Seminars (04461, 06501, 09041, 12041, 15031 and 18031) that were focused on Multiobjective Optimization. The continuing goal of this series is to strengthen the links between the Evolutionary Multiobjective Optimization (EMO) and the Multiple Criteria Decision Making (MCDM) communities, two of the largest communities concerned with multiobjective optimization today. This report documents the program and the outcomes of Dagstuhl Seminar 20031 "Scalability in Multiobjective Optimization". The seminar focused on three main aspects of scalability in multiobjective optimization (MO) and their interplay, namely (1) MO with many objective functions, (2) MO with many decision makers, and (3) MO with many variables and large amounts of data.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Mathematical optimization
  • Applied computing → Operations research
  • Computing methodologies → Artificial intelligence
  • multiple criteria decision making
  • evolutionary multiobjective optimization
  • scalability


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