Improved complexity results for the robust mean absolute deviation problem on networks with linear vertex weights

In a recent paper [10], an algorithmic approach was presented for the robust (minmax regret) absolute deviation location problem on networks with vertex weights which are linear functions of an uncertain or dynamically changing parameter. In this paper, we present algorithmic and analytical improvements that significantly reduce the computational complexity bounds for the algorithm.