On the approximate tradeoff for bicriteria batching and parallel machine scheduling problems

  • Authors:
  • Eric Angel;Evripidis Bampis;Alexander Kononov

  • Affiliations:
  • LaMI, CNRS-UMR 8042, Blvd François Mitterand, Université d'Évry Val-d'Essonne, 91025 Evry, Cedex, France;LaMI, CNRS-UMR 8042, Blvd François Mitterand, Université d'Évry Val-d'Essonne, 91025 Evry, Cedex, France;LaMI, CNRS-UMR 8042, Blvd François Mitterand, Université d'Évry Val-d'Essonne, 91025 Evry, Cedex, France and Sobolev Institute of Mathematics, Novosibirsk, Russia

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2003

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Abstract

We consider multiobjective scheduling problems, i.e. scheduling problems that are evaluated with respect to many cost criteria, and we are interested in determining a trade-off (Pareto curve) among these criteria. We study two types of bicriteria scheduling problems: single-machine batching problems and parallel machine scheduling problems. Instead of proceeding in a problem-by-problem basis, we identify a class of multiobjective optimization problems possessing a fully polynomial time approximation scheme (FPTAS) for computing an ε-approximate Pareto curve. This class contains a set of problems whose Pareto curve can be computed via a simple pseudo-polynomial dynamic program for which the objective and transition functions satisfy some, easy to verify, arithmetical conditions. Our study is based on a recent work of Woeginger (Electronic Colloquium on Computational Complexity, Report 84 (short version appeared in SODA'99, pp. 820-829)) for the single criteria optimization ex-benevolent problems. We show how our general result can be applied to the considered scheduling problems.