Covering Pareto Sets by Multilevel Subdivision Techniques
By Michael Dellnitz, Oliver Schütze, T. Hestermeyer. 2005
188 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Control and Systems Engineering, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/02d29caef804e370b59d2716f05a0ccaf9e660fe
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Yaochu Jin
- Ran Cheng
- Xing-yi Zhang
- Ye Tian
- Bernhard Sendhoff
- André H. Deutz
- Michael T. M. Emmerich
- Carlos Artemio Coello Coello
In Control and Systems Engineering
- Michael T. M. Emmerich
- André H. Deutz
- Adanay Martín
- Bernhard Sendhoff
- Carlos Artemio Coello Coello
- Oliver Schütze
- Yaochu Jin
- Ran Cheng
In Statistics and Probability
- Yaochu Jin
- Bernhard Sendhoff
- André H. Deutz
- Michael T. M. Emmerich
- Adanay Martín
- Carlos Artemio Coello Coello
- Oliver Schütze
- Ran Cheng
Citations in the corpus
- Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization (2012, methodology): “Here, we have used the multiobjective continuation method proposed in [13] and [42] together with the step size control discussed in Section IV-B.”
- Pareto Tracer: a predictor–corrector method for multi-objective optimization problems (2018, methodology): “There are also set oriented methods such as evolutionary strategies (Deb, 2001) and subdivision techniques (Dellnitz, Schutze, and Hestermeyer, 2005; Jahn, 2006), which instead use populations that gradually approximate to the solution set.”
- A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling (2015, background): “One specific observation related to regularity is the Karush-Kuhn-Tucker (KKT) condition, indicating that both PF and PS are ( m − 1)-D piecewise continuous manifolds [45] form-objective optimization problem under certain mild conditions.”
- A tutorial on multiobjective optimization: fundamentals and evolutionary methods (2018, methodology): “See Hillermeier (2001) and Schu¨tze et al. (2005) for examples and more detailed descriptions.”