A large neighborhood search heuristic for the longest common subsequence problem

被引：0
|
作者：
Todd Easton
Abhilash Singireddy
机构：
[1] Kansas State University,School of Industrial and Manufacturing Systems Engineering
来源：
Journal of Heuristics | 2008年 / 14卷
关键词：
Longest common subsequence; Dynamic programming; Large neighborhood search; Heuristic;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Given a set S={S1,…,Sk} 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 Si for i=1,…,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.
引用
收藏
页码：271 / 283
页数：12
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