Searching for Robust Pareto-Optimal Solutions in Multi-objective Optimization
By Kalyanmoy Deb, Himanshu Gupta. 2005
277 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability
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
- Kalyanmoy Deb
- Aravind Srinivasan
- Himanshu Gupta
- Ralph E. Steuer
- Yaochu Jin
- Hisao Ishibuchi
- Carlos Artemio Coello Coello
- Ran Cheng
In Management Science and Operations Research
- Kalyanmoy Deb
- Aravind Srinivasan
- Ralph E. Steuer
- Nicolas Huck
- Yaochu Jin
- Jafar Rezaei
- Matteo Brunelli
- Ran Cheng
In Statistics and Probability
Citations in the corpus
- Exploring Example Influence in Continual Learning (2022, neutral): “This can be seen as a Dual-Objective Optimization (DOO) problem, which aims to find solutions not dominated (no other better solution) by any other one, i.e. Pareto optimal solutions [8].”
- Innovization: innovating design principles through optimization (2006, background): “Finally, it is also worth mentioning that similar to the expectation of common properties to exist among Pareto-optimal solutions (as discovered and demonstrated amply in this paper), commonality principles may also be expected to exist in other kinds of trade-o solutions, such as among weakly Paret”
- Introducing Robustness in Multi-Objective Optimization (2006, background): “Recently, we suggested two different ways of introducing robustness in multiobjective optimization and showed some proof-of-principle results on unconstrained test problems (Deb and Gupta, 2005).”
- Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead (2008, background): “MCDM robustness research, see Roy (1998), Kouvelis and Sayin (2006), Deb and Gupta (2005) , and”