Empirical Investigations of Reference Point Based Methods When Facing a Massively Large Number of Objectives: First Results

Ke Li, Kalyanmoy Deb, Okkes Tolga Altinöz, Xin Yao. Empirical Investigations of Reference Point Based Methods When Facing a Massively Large Number of Objectives: First Results. In Heike Trautmann, Günter Rudolph, Kathrin Klamroth, Oliver Schütze, Margaret M. Wiecek, Yaochu Jin, Christian Grimme, editors, Evolutionary Multi-Criterion Optimization - 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. Volume 10173 of Lecture Notes in Computer Science, pages 390-405, Springer, 2017. [doi]

@inproceedings{LiDAY17,
  title = {Empirical Investigations of Reference Point Based Methods When Facing a Massively Large Number of Objectives: First Results},
  author = {Ke Li and Kalyanmoy Deb and Okkes Tolga Altinöz and Xin Yao},
  year = {2017},
  doi = {10.1007/978-3-319-54157-0_27},
  url = {http://dx.doi.org/10.1007/978-3-319-54157-0_27},
  researchr = {https://researchr.org/publication/LiDAY17},
  cites = {0},
  citedby = {0},
  pages = {390-405},
  booktitle = {Evolutionary Multi-Criterion Optimization - 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings},
  editor = {Heike Trautmann and Günter Rudolph and Kathrin Klamroth and Oliver Schütze and Margaret M. Wiecek and Yaochu Jin and Christian Grimme},
  volume = {10173},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-54156-3},
}