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A Lagrangian Relaxation Based Forward-Backward Improvement Heuristic for Maximising the Net Present Value of Resource-Constrained Projects

  • Conference paper
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7874))

Abstract

In this paper we propose a forward-backward improvement heuristic for the variant of resource-constrained project scheduling problem aiming to maximise the net present value of a project. It relies on the Lagrangian relaxation method to generate an initial set of schedules which are then improved by the iterative forward/backward scheduling technique. It greatly improves the performance of the Lagrangian relaxation based heuristics in the literature and is a strong competitor to the best meta-heuristics. We also embed this heuristic into a state-of-the-art CP solver. Experimentation carried out on a comprehensive set of test data indicates we compare favorably with the state of the art.

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Authors and Affiliations

  1. National ICT Australia, Department of Computing and Information Systems, The University of Melbourne, Victoria, 3010, Australia

    Hanyu Gu, Andreas Schutt & Peter J. Stuckey

Authors
  1. Hanyu Gu
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  2. Andreas Schutt
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  3. Peter J. Stuckey
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Cornell University, Ithaca, NY, USA

    Carla Gomes

  2. Thomas J. Watson Research Center, Yorktown Heights, NY, USA

    Meinolf Sellmann

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Gu, H., Schutt, A., Stuckey, P.J. (2013). A Lagrangian Relaxation Based Forward-Backward Improvement Heuristic for Maximising the Net Present Value of Resource-Constrained Projects. In: Gomes, C., Sellmann, M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2013. Lecture Notes in Computer Science, vol 7874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38171-3_24

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  • DOI: https://doi.org/10.1007/978-3-642-38171-3_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38170-6

  • Online ISBN: 978-3-642-38171-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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