Journal of Combinatorial Optimization

, Volume 35, Issue 2, pp 331–340 | Cite as

The longest commonly positioned increasing subsequences problem



Based on the well-known longest increasing subsequence problem and longest common increasing subsequence (LCIS) problem, we propose the longest commonly positioned increasing subsequences (LCPIS) problem. Let \(A=\langle a_1,a_2,\ldots ,a_n\rangle \) and \(B{=}\left\langle b_1,b_2,\ldots ,b_n\right\rangle \) be two input sequences. Let \({ Asub}=\left\langle a_{i_1},a_{i_2},\ldots ,a_{i_l}\right\rangle \) be a subsequence of A and \({ Bsub}=\left\langle b_{j_1},b_{j_2},\ldots ,b_{j_l}\right\rangle \) be a subsequence of B such that \(a_{i_k}\le a_{i_{k+1}}, b_{j_k}\le b_{j_{k+1}}(1\le k<l)\), and \(a_{i_k}\) and \(b_{j_k}\) (\(1\le k\le l\)) are commonly positioned (have the same index \(i_k=j_k\)) in A and B respectively but these two elements do not need to be equal. The LCPIS problem aims at finding a pair of subsequences Asub and \({ Bsub}\) as long as possible. When all the elements of the two input sequences are positive integers, this paper presents an algorithm with \(O(n\log n \log \log M)\) time to compute the LCPIS, where \(M={ min}\{{ max}_{1\le i\le n}a_i,{ max}_{1\le j\le n}b_j\}\). And we also show a dual relationship between the LCPIS problem and the LCIS problem.


Longest increasing subsequence Common positions Algorithms Dual relationship Longest common increasing subsequence 



This research was supported by the National Natural Science Foundation of China under Grant 71371129.


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© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Business SchoolSichuan UniversityChengduChina
  2. 2.State Key Lab for Manufacturing Systems EngineeringXi’anChina

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