Solving the bi-objective maximum-flow network-interdiction problem

We describe a new algorithm for computing the efficient frontier of the bi-objective maximum-flow network-interdiction problem. In this problem, an interdictor seeks to interdict (destroy) a set of arcs in a capacitated network that are Pareto-optimal with respect to two objectives, minimizing total interdiction cost and minimizing maximum flow. The algorithm identifies these solutions through a sequence of single-objective problems solved using Lagrangian relaxation and a specialized branch-and-bound algorithm. The Lagrangian problems are simply max-flow min-cut problems, while the branch-and-bound procedure partially enumerates s-t cuts. Computational tests reveal the new algorithm to be one to two orders of magnitude faster than an algorithm that replaces the specialized branch-and-bound algorithm with a standard integer-programming solver.