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Algorithms and Linear Programming Relaxations for Scheduling Unrelated Parallel Machines

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Experimental Algorithms (SEA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7933))

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Abstract

Since the early days of combinatorial optimization, algorithms and techniques from the closely related area of mathematical programming have played a pivotal role in solving combinatorial optimization problems. This holds both for ‘easy’ problems that can be solved efficiently in polynomial time, such as, e. g., the weighted matching problem [3], as well as for NP-hard problems whose solution might take exponential time in the worst case, such as, e. g., the traveling salesperson problem [1].

Supported by the DFG Research Center Matheon “Mathematics for key technologies” in Berlin and by the DFG Focus Program 1307 within the project “Algorithm Engineering for Real-time Scheduling and Routing”.

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Authors and Affiliations

  1. Fakultät II – Mathematik und Naturwissenschaften, Institut für Mathematik, Sekr. MA 5-2, Technische Universität Berlin, Straße des 17. Juni 136, 10623, Berlin, Germany

    Martin Skutella

Authors
  1. Martin Skutella
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Editors and Affiliations

  1. Institute for Systems Analysis and Computer Science (IASI), National Research Council (CNR), Viale Manzoni 30, 00185, Rome, Italy

    Vincenzo Bonifaci

  2. Department of Computer and Systems Science, Sapienza University of Rome, Via Ariosto 25, 00185, Rome, Italy

    Camil Demetrescu  & Alberto Marchetti-Spaccamela  & 

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Skutella, M. (2013). Algorithms and Linear Programming Relaxations for Scheduling Unrelated Parallel Machines. In: Bonifaci, V., Demetrescu, C., Marchetti-Spaccamela, A. (eds) Experimental Algorithms. SEA 2013. Lecture Notes in Computer Science, vol 7933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38527-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-38527-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38526-1

  • Online ISBN: 978-3-642-38527-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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