  A hypergraph is a set V of vertices and a set of non-empty subsets of V,
called hyperedges. Unlike graphs, hypergraphs can capture higher-order
interactions in social and communication networks that go beyond a simple union
of pairwise relationships. In this paper, we consider the shortest path problem
in hypergraphs. We develop two algorithms for finding and maintaining the
shortest hyperpaths in a dynamic network with both weight and topological
changes. These two algorithms are the first to address the fully dynamic
shortest path problem in a general hypergraph. They complement each other by
partitioning the application space based on the nature of the change dynamics
and the type of the hypergraph.
