Computing Diverse Shortest Paths Efficiently: A Theoretical and Experimental Study

Tesshu Hanaka, Yasuaki Kobayashi, Kazuhiro Kurita, See Woo Lee, Yota Otachi. Computing Diverse Shortest Paths Efficiently: A Theoretical and Experimental Study. In Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence, IAAI 2022, The Twelveth Symposium on Educational Advances in Artificial Intelligence, EAAI 2022 Virtual Event, February 22 - March 1, 2022. pages 3758-3766, AAAI Press, 2022. [doi]

@inproceedings{HanakaKKLO22,
  title = {Computing Diverse Shortest Paths Efficiently: A Theoretical and Experimental Study},
  author = {Tesshu Hanaka and Yasuaki Kobayashi and Kazuhiro Kurita and See Woo Lee and Yota Otachi},
  year = {2022},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/20290},
  researchr = {https://researchr.org/publication/HanakaKKLO22},
  cites = {0},
  citedby = {0},
  pages = {3758-3766},
  booktitle = {Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence, IAAI 2022, The Twelveth Symposium on Educational Advances in Artificial Intelligence, EAAI 2022 Virtual Event, February 22 - March 1, 2022},
  publisher = {AAAI Press},
  isbn = {978-1-57735-876-3},
}