branch and bound optimization in an exhaustive search, all possible trees in a search space are...
Post on 16-Dec-2015
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Branch and Bound Branch and Bound OptimizationOptimization
• In an exhaustive search, all possible trees in a search space are generated for comparison
• At each node, if the tree is optimal we retain it• As the number of taxa becomes large, this
approach becomes intractable• Thus, there is a need for an approach that can
effectively prune the search space so that finding solution may become more feasible
• One such approach is the branch-and-bound method
Exhaustive SearchExhaustive Search• Search for optimal trees
by evaluating every possible tree
• Feasible only for <=11 taxa, as processing costs rapidly increase after that
• Figure shows exhaustive search for a 5-taxa tree
Branch and BoundBranch and Bound• Focuses on pruning the search space by ignoring families of trees
that can not possible produce a better answer than the best one already found
• Traverse a search tree in a depth-first sequence
• Trees that have longer tree length than the previously examined ones are ignored
• MP (Maximum Parsimony tree, i.e. the topology with the minimum tree length) is determined by evaluating tree lengths for a group of trees that have potentially shorter length
• Faster than an exhaustive search, but still impractical for large numbers of taxa
Branch and Bound Branch and Bound MethodologyMethodology
• When a node is encountered that has a higher tree-length than the minimum tree length, all the subsequent expansions for the tree are pruned away
• This corresponds to taking a subset of m taxa, where m<n (n = current minimum found) and computing tree length
• If this tree length is larger than the tree length we have for any n taxa configuration, the m tree topology and all its children are aborted from further consideration
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