Minimizing worst-case and average-case makespan over scenarios

Esteban Feuerstein, Alberto Marchetti-Spaccamela, Frans Schalekamp, René Sitters, Suzanne Ster (), Leen Stougie and Anke Zuylen
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Esteban Feuerstein: Universidad de Buenos Aires
Alberto Marchetti-Spaccamela: Sapienza Università di Roma
Frans Schalekamp: Cornell University
René Sitters: Vrije Universiteit & CWI
Suzanne Ster: Technische Universität München
Leen Stougie: Vrije Universiteit & CWI
Anke Zuylen: College of William and Mary

Journal of Scheduling, 2017, vol. 20, issue 6, No 2, 545-555

Abstract: Abstract We consider scheduling problems over scenarios where the goal is to find a single assignment of the jobs to the machines which performs well over all scenarios in an explicitly given set. Each scenario is a subset of jobs that must be executed in that scenario. The two objectives that we consider are minimizing the maximum makespan over all scenarios and minimizing the sum of the makespans of all scenarios. For both versions, we give several approximation algorithms and lower bounds on their approximability. We also consider some (easier) special cases. Combinatorial optimization problems under scenarios in general, and scheduling problems under scenarios in particular, have seen only limited research attention so far. With this paper, we make a step in this interesting research direction.

Keywords: Job scheduling; Approximation algorithm; Makespan; Scenarios (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10951-016-0484-y

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