A GRASP algorithm for the Closest String Problem using a probabilitybased heuristic

The Closest String Problem (CSP) is the problem of finding a string whose Hamming distance from the members of a given set of strings of the same length is minimal. It has applications, among others, in bioinformatics and in coding theory. Several approximation and (meta)heuristic algorithms have be...

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Bibliographic Details
Published inComputers & operations research Vol. 39; no. 2; p. 238
Main Authors Mousavi, Sayyed Rasoul, Esfahani, Navid Nasr
Format Journal Article
LanguageEnglish
Published New York Pergamon Press Inc 01.02.2012
Subjects
Algorithms
Approximation
Hamming codes
Heuristic
Optimization algorithms
Studies
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Summary:The Closest String Problem (CSP) is the problem of finding a string whose Hamming distance from the members of a given set of strings of the same length is minimal. It has applications, among others, in bioinformatics and in coding theory. Several approximation and (meta)heuristic algorithms have been proposed for the problem to achieve 'good' but not necessarily optimal solutions within a reasonable time. In this paper, a new algorithm for the problem is proposed, based on a Greedy Randomized Adaptive Search Procedure (GRASP) and a novel probabilistic heuristic function. The algorithm is compared with three recently proposed algorithms for CSP, outperforming all of them by achieving solutions of higher quality within a few seconds in most of the experimental cases. [PUBLICATION ABSTRACT]
ISSN:0305-0548
0305-0548