Abstract. In this paper, we propose a general framework for designing fully polynomial time approximation schemes for combinatorial optimization problems, in which more than one ob...
Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workfor...
We study algorithmic problems that are motivated by bandwidth trading in next generation networks. Typically, bandwidth trading involves sellers (e.g., network operators) interest...
Randeep Bhatia, Julia Chuzhoy, Ari Freund, Joseph ...
We define an algorithmic paradigm, the stack model, that captures many primal-dual and local-ratio algorithms for approximating covering and packing problems. The stack model is ...
We provide several non-approximability results for deterministic scheduling problems whose objective is to minimize the total job completion time. Unless P = NP, none of the probl...
Han Hoogeveen, Petra Schuurman, Gerhard J. Woeging...