An enhanced beam search algorithm for the Shortest Common Supersequence Problem.

The Shortest Common Supersequence Problem asks to obtain a shortest string that is a supersequence of every member of a given set of strings. It has applications, among others, in data compression and oligonucleotide microarray production. The problem is NP-hard, and the existing exact solutions are impractical for large instances.

A hyper-heuristic for the Longest Common Subsequence problem.

The Longest Common Subsequence Problem is the problem of finding a longest string that is a subsequence of every member of a given set of strings. It has applications in FPGA circuit minimization, data compression, and bioinformatics, among others. The problem is NP-hard in its general form, which implies that no exact polynomial-time algorithm currently exists for the problem.

A hybrid metaheuristic for closest string problem.

The Closest String Problem (CSP) is an optimisation problem, which is to obtain a string with the minimum distance from a number of given strings. In this paper, a new metaheuristic algorithm is investigated for the problem, whose main feature is relatively high speed in obtaining good solutions, which is essential when the input size is large. The proposed algorithm is compared with four recent algorithms suggested for the problem, outperforming them in more than 98% of the cases.