Back to Search Start Over

The balanced minimum evolution problem under uncertain data

Authors :
Daniele Catanzaro
Martine Labbé
Raffaele Pesenti
Research programme OPERA
Fortz, Bernard
Dipartimento di Management
University of Ca’ Foscari [Venice, Italy]
Graphes et Optimisation Mathématique [Bruxelles] (GOM)
Université libre de Bruxelles (ULB)
Source :
Discrete Applied Mathematics, 161(13-14), 1789-1804, Discrete Applied Mathematics, Discrete Applied Mathematics, Elsevier, 2013, 161 (13-14), pp.1789-1804
Publication Year :
2013

Abstract

We investigate the Robust Deviation Balanced Minimum Evolution Problem (RDBMEP), a combinatorial optimization problem that arises in computational biology when the evolutionary distances from taxa are uncertain and varying inside intervals. By exploiting some fundamental properties of the objective function, we present a mixed integer programming model to exactly solve instances of the RDBMEP and discuss the biological impact of uncertainty on the solutions to the problem. Our results give perspective on the mathematics of the RDBMEP and suggest new directions to tackle phylogeny estimation problems affected by uncertainty. (c) 2013 Elsevier B.V. All rights reserved.

Details

Language :
English
ISSN :
0166218X
Database :
OpenAIRE
Journal :
Discrete Applied Mathematics, 161(13-14), 1789-1804, Discrete Applied Mathematics, Discrete Applied Mathematics, Elsevier, 2013, 161 (13-14), pp.1789-1804
Accession number :
edsair.doi.dedup.....57edd138f234322d36973fd184987058