ACM Transactions on Algoritms Vol.14 No.2 2018 (4 Issues)


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We consider two related scheduling problems: single resource-constrained scheduling on identical parallel machines and a generalization with resource-dependent processing times. In both problems, jobs require a certain amount of an additional resource and have to be scheduled on machines minimizing the makespan, while at every point in time a given resource capacity is not exceeded. In the first variant of the problem, the processing times and resource amounts are fixed, while in the second the former depends on the latter.

Both problems contain bin packing with cardinality constraint as a special case, and, therefore, these problems are strongly NP-complete even for a constant number of machines larger than three, which can be proven by a reduction from 3-Partition. Furthermore, if the number of machines is part of the input, then we cannot hope for an approximation algorithm with absolute approximation ratio smaller than 3/2.

We present asymptotic fully polynomial time approximation schemes (AFPTAS) for the problems: For any ϵ > 0, a schedule of length at most (1+ϵ) times the optimum plus an additive term of O(pmax log (1/ϵ)/ϵ) is provided, and the running time is polynomially bounded in 1/ϵ and the input length. Up to now, only approximation algorithms with absolute approximation ratios were known. Furthermore, the AFPTAS for resource-constrained scheduling on identical parallel machines directly improves the additive term of the best AFPTAS for bin packing with cardinality constraint so far.

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ACM Transactions on Algorithms (TALG)






Aravind Srinivasan


ACM New York, NY, USA