Among the sequence selection and comparison problems, the Far From Most String Problem (FFMSP) is one of the computationally hardest with applications in several fields, including molecular biology where one is interested in creating diagnostic probes for bacterial infections or in discovering potential drug targets. In this article, several hybrid metaheuristics are described and tested. Extensive comparative experiments on a large set of randomly generated test instances indicate that these randomized hybrid techniques are both effective and efficient.

Hybrid metaheuristics for the far from most string problem / D., Ferone; Festa, Paola; M. G. C., Resende. - 7919:(2013), pp. 174-188. [10.1007/978-3-642-38516-2_14]

Hybrid metaheuristics for the far from most string problem

D. Ferone;FESTA, PAOLA;
2013

Abstract

Among the sequence selection and comparison problems, the Far From Most String Problem (FFMSP) is one of the computationally hardest with applications in several fields, including molecular biology where one is interested in creating diagnostic probes for bacterial infections or in discovering potential drug targets. In this article, several hybrid metaheuristics are described and tested. Extensive comparative experiments on a large set of randomly generated test instances indicate that these randomized hybrid techniques are both effective and efficient.
2013
9783642385155
Hybrid metaheuristics for the far from most string problem / D., Ferone; Festa, Paola; M. G. C., Resende. - 7919:(2013), pp. 174-188. [10.1007/978-3-642-38516-2_14]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/564175
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? ND
social impact