English

The Dynamic Longest Increasing Subsequence Problem

Data Structures and Algorithms 2013-12-17 v4

Abstract

In this paper, we construct a data structure to efficiently compute the longest increasing subsequence of a sequence subject to dynamic updates. Our data structure supports a query for the longest increasing subsequence in O(r+logn)O(r+\log n) worst-case time and supports inserts anywhere in the sequence in O(rlogn/r)O \left(r\log{n/r}\right) worst-case time (where rr is the length of the longest increasing subsequence). The same data structure with a minor modification supports O(logn)O(\log n) worst-case time insertions if the insertions are performed at the end of the sequence. The data structure presented can also be augmented to support delete operations in the same worst-case time as insertions.

Keywords

Cite

@article{arxiv.1309.7724,
  title  = {The Dynamic Longest Increasing Subsequence Problem},
  author = {Alex Chen and Timothy Chu and Nathan Pinsker},
  journal= {arXiv preprint arXiv:1309.7724},
  year   = {2013}
}
R2 v1 2026-06-22T01:36:49.291Z