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Maximising the Net Present Value of Project Schedules Using CMSA and Parallel ACO

  • Dhananjay ThiruvadyEmail author
  • Christian Blum
  • Andreas T. Ernst
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11299)

Abstract

This study considers the problem of resource constrained project scheduling to maximise the net present value. A number of tasks must be scheduled within a fixed time horizon. Tasks may have precedences between them and they use a number of common resources when executing. For each resource, there is a limit, and the cumulative resource requirements of all tasks executing at the same time must not exceed the limits. To solve this problem, we develop a hybrid of Construct, Merge, Solve and Adapt (CMSA) and Ant Colony Optimisation (ACO). The methods are implemented in a parallel setting within a multi-core shared memory architecture. The results show that the proposed algorithm outperforms the previous state-of-the-art method, a hybrid of Lagrangian relaxation and ACO.

Keywords

Project scheduling Net present value Construct Merge Solve & Adapt Ant Colony Optimisation 

Notes

Acknowledgements

This research was supported in part by the Monash eResearch Centre and eSolutions-Research Support Services through the use of the MonARCH HPC Cluster.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Dhananjay Thiruvady
    • 1
  • Christian Blum
    • 2
  • Andreas T. Ernst
    • 1
  1. 1.School of Mathematical SciencesMonash UniversityMelbourneAustralia
  2. 2.Artificial Intelligence Research Institute (IIIA-CSIC)BellaterraSpain

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