In the k-center problem, given a metric space V and a positive integer k, one wants to select k elements (centers) of V and an assignment from V to centers, minimizing the maximum distance between an element of V and its assigned center. One of the most general variants is the capacitated α-fault-tolerant k-center, where centers have a limit on the number of assigned elements, and, if any α centers fail, there is a reassignment from V to non-faulty centers. In this paper, we present a new approach to tackle fault tolerance, by selecting and pre-opening a set of backup centers, then solving the obtained residual instance. For the {0, L}-capacitated case, we give approximations with factor 6 for the basic problem, and 7 for the so called conservative variant, when only clients whose centers failed may be reassigned. Our algorithms improve on the best previously known factors of 9 and 17, respectively. Moreover, we consider the case with general capacities. Assuming α is constant, our method leads to the first approximations for this case. We also derive approximations for the capacitated fault-tolerant k-supplier problem.
Recently, REF also provided constant approximations for the fault-tolerant capacitated k-center clustering.
Improved Approximation Algorithms for Capacitated Fault-Tolerant k-Center
Algorithmica
Algorithmica
Mathematics Computer Science