  This paper discusses the fixed-hub single allocation problem (FHSAP). In this
problem, a network consists of hub nodes and terminal nodes. Hubs are fixed and
fully connected; each terminal node is connected to a single hub which routes
all its traffic. The goal is to minimize the cost of routing the traffic in the
network. In this paper, we propose a linear programming (LP)-based rounding
algorithm. The algorithm is based on two ideas. First, we modify the LP
relaxation formulation introduced in Ernst and Krishnamoorthy (1996, 1999) by
incorporating a set of validity constraints. Then, after obtaining a fractional
solution to the LP relaxation, we make use of a geometric rounding algorithm to
obtain an integral solution. We show that by incorporating the validity
constraints, the strengthened LP often provides much tighter upper bounds than
the previous methods with a little more computational effort, and the solution
obtained often has a much smaller gap with the optimal solution. We also
formulate a robust version of the FHSAP and show that it can guard against data
uncertainty with little cost.
