Improvements in Throughput Maximization for Real-Time Scheduling

We consider the problem of off-line throughput maximization for job scheduling on one or more machines, where each job has a release time, a deadline and a profit. Most of the versions of the problem discussed here were already treated by Bar-Noy et al. [3]. Our main contribution is to provide algorithms that do not use linear programming, are simple and much faster than the corresponding ones proposed in [3], while either having the same quality of approximation or improving it. More precisely, compared to the results of in BarNoy et al. [3], our pseudo-polynomial algorithm for multiple unrelated machines and all of our strongly-polynomial algorithms have better performance ratios, all of our algorithms run much faster, are combinatorial in nature and avoid linear programming. Finally, we show that algorithms with better performance ratios than 2 are possible if the stretch factors of the jobs are bounded; a straightforward consequence of this result is an improvement of the ratio of an optimal solution to the integer programming formulation of the JISP2 problem (see [13]) to that of its linear programming relaxation.