A parallel multistart algorithm for the closest string problem

Authors:
Fernando C. Gomes;Cláudio N. Meneses;Panos M. Pardalos;Gerardo Valdisio R. Viana
Affiliations:
Department of Computer Science, Federal University of Ceara, Brazil;Department of Industrial and Systems Engineering, University of Florida, 303 Weil Hall, Gainesville, FL 32611, USA;Department of Industrial and Systems Engineering, University of Florida, 303 Weil Hall, Gainesville, FL 32611, USA;Department of Computer Science, Federal University of Ceara, Brazil and Computer Science Department, State University of Ceara, Brazil
Venue:
Computers and Operations Research
Year:
2008

Citing 6
Cited 5

Random number generators: good ones are hard to find

Communications of the ACM
Efficient approximation algorithms for the Hamming center problem

Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
On the closest string and substring problems

Journal of the ACM (JACM)
Banishing Bias from Consensus Sequences

CPM '97 Proceedings of the 8th Annual Symposium on Combinatorial Pattern Matching
Distinguishing string selection problems

Information and Computation
Optimal Solutions for the Closest-String Problem via Integer Programming

INFORMS Journal on Computing

Ant-CSP: An Ant Colony Optimization Algorithm for the Closest String Problem

SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
Exact algorithm and heuristic for the Closest String Problem

Computers and Operations Research
A GRASP algorithm for the Closest String Problem using a probability-based heuristic

Computers and Operations Research
A heuristic algorithm based on Lagrangian relaxation for the closest string problem

Computers and Operations Research
An improved heuristic for the far from most strings problem

Journal of Heuristics

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper we describe and implement a parallel algorithm to find approximate solutions for the Closest String Problem (CSP). The CSP, also known as Motif Finding problem, has applications in Coding Theory and Computational Biology. The CSP is NP-hard which motivates us to think about heuristics to solve large instances. Several approximation algorithms have been designed for the CSP, but all of them have a poor performance guarantee. Recently some researchers have shown empirically that integer programming techniques can be successfully used to solve moderate-size instances (10-30 strings each of which is 300-800 characters long) of the CSP. However, real-world instances are larger than those tested. In this paper we show how a simple heuristic can be used to find near-optimal solutions to that problem. We implemented a parallel version of this heuristic and report computational experiments on large-scale instances. These results show the effectiveness of our approach.