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Convex Quadratic Programming in Scheduling

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Gems of Combinatorial Optimization and Graph Algorithms

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Abstract

We consider the optimization problem of scheduling a given set of jobs on unrelated parallel machines with total weighted completion time objective. This is a classical scheduling problem known to be NP-hard since the 1970s. We give a new and simplified version of the currently best-known approximation algorithm, which dates back to 1998. It achieves performance ratio 3 / 2, and is based on an optimal solution to a convex quadratic program.

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Author information

Authors and Affiliations

  1. Institut für Mathematik, Technische Universität Berlin, Straße des 17. Juni 136, 10623, Berlin, Germany

    Martin Skutella

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  1. Martin Skutella
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Correspondence to Martin Skutella .

Editor information

Editors and Affiliations

  1. Technische Universität München, Munich, Germany

    Andreas S. Schulz

  2. Institute of Mathematics, Technische Universität Berlin, Berlin, Berlin, Germany

    Martin Skutella

  3. Technische Universität Braunschweig, Braunschweig, Germany

    Sebastian Stiller

  4. Institute of Theoretical Informatics, Karlsruher Institut für Technologie (KIT), Karlsruhe, Germany

    Dorothea Wagner

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Skutella, M. (2015). Convex Quadratic Programming in Scheduling. In: Schulz, A., Skutella, M., Stiller, S., Wagner, D. (eds) Gems of Combinatorial Optimization and Graph Algorithms . Springer, Cham. https://doi.org/10.1007/978-3-319-24971-1_12

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