Parsimonious phylogenetic trees in metric spaces and simulated annealing
Advances in Applied Mathematics
Object-oriented modeling and design
Object-oriented modeling and design
Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
Pattern-oriented software architecture: a system of patterns
Pattern-oriented software architecture: a system of patterns
Object-oriented application frameworks
Communications of the ACM
Computers and Operations Research
Two Strikes Against Perfect Phylogeny
ICALP '92 Proceedings of the 19th International Colloquium on Automata, Languages and Programming
Progressive Tree Neighborhood Applied to the Maximum Parsimony Problem
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Finding consensus trees by evolutionary, variable neighborhood search, and hybrid algorithms
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Parallelisation of a multi-neighbourhood local search heuristic for a phylogeny problem
International Journal of Bioinformatics Research and Applications
A Memetic Algorithm for Phylogenetic Reconstruction with Maximum Parsimony
EvoBIO '09 Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
On the application of evolutionary algorithms to the consensus tree problem
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Local search for the maximum parsimony problem
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
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A phylogeny is a tree that relates taxonomic units, based on their similarity over a set of characters. The problem of finding a phylogeny with the minimum number of evolutionary steps (the so-called parsimony criterion) is one of the main problems in comparative biology. In this work, we study different heuristic approaches to the phylogeny problem under the parsimony criterion. New algorithms based on metaheuristics are also proposed. All heuristics are implemented and compared under the same framework, leading to consistent and thorough comparative results. Computational results are reported for benchmark instances from the literature.