A NEAR-OPTIMAL ALGORITHM FOR SHORTEST PATHS AMONG CURVED OBSTACLES IN THE PLANE


Hershberger J., Suri S., YILDIZ H.

SIAM Journal on Computing, cilt.51, sa.4, ss.1296-1340, 2022 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 51 Sayı: 4
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1137/21m1428248
  • Dergi Adı: SIAM Journal on Computing
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Agricultural & Environmental Science Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, INSPEC, MathSciNet, zbMATH
  • Sayfa Sayıları: ss.1296-1340
  • Anahtar Kelimeler: geometric obstacles, obstacle avoidance, planar subdivision, shortest path map, shortest paths
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

© 2022 Society for Industrial and Applied Mathematics.We propose an algorithm for the problem of computing shortest paths among curved obstacles in the plane. If the obstacles have O(n) description complexity, then the algorithm runs in O(n log n) time plus a term dependent on the properties of the boundary arcs. Specifically, if the arcs allow a certain kind of bisector intersection to be computed in constant time, or even in O(log n) time, then the running time of the overall algorithm is O(n log n). If the arcs support only constant-time tangent, intersection, and length queries, as is customarily assumed, then the algorithm computes an approximate shortest path, with relative error ε, in time O(n log n + n log 1\e ). In fact, the algorithm computes an approximate shortest path map, a data structure with O(n log n) size, that allows it to report the (approximate) length of a shortest path from a fixed source point to any query point in the plane in O(log n) time. By applying an idea due to Wang [Proceedings of the 32nd Annual ACM-SIAM Symposium on Discrete Algorithms, 2021, pp. 810-821], the algorithm's working storage and the size of the approximate shortest path map can be reduced to O(n).