Approximation algorithms for scheduling unrelated parallel machines
Mathematical Programming: Series A and B
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Algorithms for Scheduling Tasks on Unrelated Processors
Journal of the ACM (JACM)
Scheduling Tasks on Unrelated Machines: Large Neighborhood Improvement Procedures
Journal of Heuristics
Parallel Machine Scheduling by Column Generation
Operations Research
Single-source unsplittable flow
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Improving time bounds on maximum generalised flow computations by contracting the network
Theoretical Computer Science - Special issue on automata, languages and programming
Computing Nash equilibria for scheduling on restricted parallel links
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Speeding-up linear programming using fast matrix multiplication
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
A faster combinatorial approximation algorithm for scheduling unrelated parallel machines
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
An optimal rounding gives a better approximation for scheduling unrelated machines
Operations Research Letters
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Scheduling n independent jobs on m unrelated parallel machines without preemption belongs to the most difficult scheduling problems. Here, processing job i on machine j takes time pij, and the total time used by a machine is the sum of the processing times for the jobs assigned to it. The objective is to minimize makespan. In this paper we present an experimental study on the Unsplittable-Truemper algorithm. This purely combinatorial approach computes 2-approximate solutions in the best worst-case running time known so far. The goal of our simulations was to prove its efficiency in practice. We compare our technique with algorithms and heuristics used in practice, especially with those based on the two-step approach. The experiments show that for large and difficult instances the Unsplittable-Truemper algorithm has a clear advantage over methods based on linear programming. Moreover, it requires much less operational memory, and thus is more effective and easier to handle.