A large neighborhood search heuristic for the longest common subsequence problem

Authors:
Todd Easton;Abhilash Singireddy
Affiliations:
School of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, USA 66506;School of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, USA 66506
Venue:
Journal of Heuristics
Year:
2008

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Abstract

Given a set S={S 1,驴,S k } of finite strings, the k-Longest Common Subsequence Problem (k-LCSP) seeks a string L * of maximum length such that L * is a subsequence of each S i for i=1,驴,k. This paper presents a large neighborhood search technique that provides quality solutions to large k-LCSP instances. This heuristic runs in linear time in both the length of the sequences and the number of sequences. Some computational results are provided.