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Approximation Results for Makespan Minimization with Budgeted Uncertainty

  • Marin BougeretEmail author
  • Klaus Jansen
  • Michael Poss
  • Lars Rohwedder
Conference paper
  • 80 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11926)

Abstract

We study approximation algorithms for the problem of minimizing the makespan on a set of machines with uncertainty on the processing times of jobs. In the model we consider, which goes back to [3], once the schedule is defined an adversary can pick a scenario where deviation is added to some of the jobs’ processing times. Given only the maximal cardinality of these jobs, and the magnitude of potential deviation for each job, the goal is to optimize the worst-case scenario. We consider both the cases of identical and unrelated machines. Our main result is an EPTAS for the case of identical machines. We also provide a 3-approximation algorithm and an inapproximability ratio of \(2-\epsilon \) for the case of unrelated machines.

Keywords

Makespan minimization Robust Optimization Approximation algorithms EPTAS Parallel machines Unrelated machines 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Marin Bougeret
    • 2
    Email author
  • Klaus Jansen
    • 1
  • Michael Poss
    • 2
  • Lars Rohwedder
    • 1
  1. 1.Department of Computer ScienceKiel UniversityKielGermany
  2. 2.LIRMMUniversity of Montpellier, CNRSMontpellierFrance

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