Distributed Modified Extremal Optimization using Island Model for Reducing Crossovers in Reconciliation Graph

To determine the mechanism of molecular evolution, molecular biologists need to carry out reconciliation work. In reconciliation work, they compare the relation between two heterogeneous phylogenetic trees and the relation between a phylogenetic tree and a taxonomic tree are compared. Phylogenetic trees and taxonomic trees are referred to as ordered trees and a reconciliation graph is constructed from two ordered trees. In the reconciliation graph, the leaf nodes of the two ordered trees face each other. Furthermore, leaf nodes with the same label name are connected to each other by an edge. To carry out reconciliation work efficiently, it is necessary to find the state with the minimum number of crossovers of edges between leaf nodes. Reducing crossovers in a reconciliation graph is the combinatorial optimization problem that finds the state with the minimum number of crossovers. In this paper, we propose a novel bio-inspired heuristic called distributed modified extremal optimization (DMEO) using the island model. This heuristic is a hybrid of population-based modified extremal optimization (PMEO) and the distributed genetic algorithm using the island model that is used for reducing crossovers in a reconciliation graph. We have evaluated DMEO using actual data sets. DMEO shows better performance compared with PMEO.