ACM Transactions on Database Systems (TODS)
Data compression: methods and theory
Data compression: methods and theory
The Complexity of Some Problems on Subsequences and Supersequences
Journal of the ACM (JACM)
Data Structures and Algorithms
Data Structures and Algorithms
A Taxonomy of Hybrid Metaheuristics
Journal of Heuristics
A Survey of Longest Common Subsequence Algorithms
SPIRE '00 Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE'00)
Area-efficient instruction set synthesis for reconfigurable system-on-chip designs
Proceedings of the 41st annual Design Automation Conference
Computers and Operations Research
A large neighborhood search heuristic for the longest common subsequence problem
Journal of Heuristics
Finding the longest common subsequence for multiple biological sequences by ant colony optimization
Computers and Operations Research
Beam search for the longest common subsequence problem
Computers and Operations Research
Guest Editorial: Hybrid Metaheuristics
Computers and Operations Research
Starting from scratch: growing longest common subsequences with evolution
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
A unified view on hybrid metaheuristics
HM'06 Proceedings of the Third international conference on Hybrid Metaheuristics
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The longest common subsequence problem is a classical string problem. It has applications, for example, in pattern recognition and bioinformatics. This contribution proposes an integrative hybrid metaheuristic for this problem. More specifically, we propose a variable neighborhood search that applies an iterated greedy algorithm in the improvement phase and generates the starting solutions by invoking either beam search or a greedy randomized procedure. The main motivation of this work is the lack of fast neighborhood search methods for the tackled problem. The benefits of the proposal in comparison to the state of the art are experimentally shown.