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Metaheuristic Approaches for Multiprocessor Scheduling

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Proceedings of the Third International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 258))

Abstract

In the multiprocessor scheduling problem, a given list of tasks has to be scheduled on identical parallel processors. Each task in the list is defined by a release date, a due date and a processing time. The objective is to minimize the number of processors used while respecting the constraints imposed by release dates and due dates. This objective is clearly linked with minimizing the cost of hardware needed for implementing a specific application. In this paper, we have proposed two metaheuristic approaches for this problem. The first approach is based on artificial bee colony algorithm, whereas the latter approach is based on invasive weed optimization algorithm. On the standard benchmark instances for the problem, performances of our approaches are comparable to other state-of-the-art approaches.

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Authors and Affiliations

  1. School of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500 046, India

    Lakshmi Kanth Munganda & Alok Singh

Authors
  1. Lakshmi Kanth Munganda
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  2. Alok Singh
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Correspondence to Alok Singh .

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Editors and Affiliations

  1. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  3. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  4. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

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Munganda, L.K., Singh, A. (2014). Metaheuristic Approaches for Multiprocessor Scheduling. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 258. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1771-8_62

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  • DOI: https://doi.org/10.1007/978-81-322-1771-8_62

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1770-1

  • Online ISBN: 978-81-322-1771-8

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