Reconciling a gene tree with a species tree is an important task that reveals much about the evolution of genes, genomes, and species, as well as about the molecular function of genes. A wide array of computational tools have been devised for this task under certain evolutionary events such as hybridization, gene duplication/loss, or incomplete lineage sorting. Work on reconciling gene tree with species phylogenies under two or more of these events have also begun to emerge. Our group recently devised both parsimony and probabilistic frameworks for reconciling a gene tree with a phylogenetic network, thus allowing for the detection of hybridization in the presence of incomplete lineage sorting. While the frameworks were general and could handle any topology, they are computationally intensive, rendering their application to large datasets infeasible. In this paper, we present two novel approaches to address the computational challenges of the two frameworks that are based on the concept of ancestral configurations. Our approaches still compute exact solutions while improving the computational time by up to five orders of magnitude. These substantial gains in speed scale the applicability of these unified reconciliation frameworks to much larger data sets. We discuss how the topological features of the gene tree and phylogenetic network may affect the performance of the new algorithms. We have implemented the algorithms in our PhyloNet software package, which is publicly available in open source.