Data structures and algorithms for (non-)dominance filtering

Researchers

Kathrin Klamroth
Bruno Lang
Miachael Stiglmayr

Duration and funding

Ongoing

Description

An important operation in multi-criteria optimization is filtering points w.r.t. (non-)dominance, i.e., eliminating points that are inferior to some other point considering all objective functions.

So far we have considered

efficient data structures (space-partitioned ND-trees), in particular for the case that the points to be filtered are generated sequentially (that is, maintaining a Pareto archive), and
algorithms for efficiently filtering the union or Minkowski sum of already filtered sets of points.

Project-related publications

[1]	Bruno Lang. Space-partitioned ND-trees for the dynamic nondominance problem. IEEE Trans. Evol. Comput., 26(4):1004--1014, October 2022. [ DOI \| Abstract ]
[2]	Kathrin Klamroth, Bruno Lang, and Michael Stiglmayr. Efficient dominance filtering for unions and Minkowski sums of non-dominated sets. 2022. [ Abstract ]

Bergische Universität Wuppertal Fakultät für Mathematik und Naturwissenschaften Angewandte Informatik - Algorithmik and IMACM

Data structures and algorithms for (non-)dominance filtering

Researchers

Duration and funding

Description

Project-related publications

See also

Bergische Universität Wuppertal
Fakultät für Mathematik und Naturwissenschaften
Angewandte Informatik - Algorithmik and IMACM