Han Hoogeveen

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We investigate the computational complexity of scheduling multiprocessor tasks with prespecified processor allocations. We consider two criteria: minimizing schedule length and minimizing the sum of the task completion times. In addition, we investigate the complexity of problems when precedence constraints or release dates are involved. KeJa ~cwd.s:(More)
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 problems under consideration can be approximated in polynomial time within arbitrarily good precision. Most of our results are derived by Max SNP hardness proofs. Among the investigated(More)
Parallel machine scheduling problems concern the scheduling of n jobs onm machines to minimize some function of the job completion times. If preemption is not allowed, then most problems are not only NPhard, but also very hard from a practical point of view. In this paper, we show that strong and fast linear programming lower bounds can be computed for an(More)
Lagrangian relaxation is a powerful bounding technique that has been applied successfully to many / /9-hard combinatorial optimization problems. The basic idea is to see an ./K~-hard problem as an "easy-to-solve" problem complicated by a number of "nasty" side constraints. We show that reformulating nasty inequality constraints as equalities by using slack(More)