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Asian Conference on Intelligent Information and Database Systems

ACIIDS 2016: Intelligent Information and Database Systems pp 286–295Cite as

Solving a Malleable Jobs Scheduling Problem to Minimize Total Weighted Completion Times by Mixed Integer Linear Programming Models

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9622))

Abstract

In this paper we report two mixed integer linear programming models to resolve the malleable jobs scheduling problem with single resource. Jobs’ release dates and deadlines are taken into account. The total amount of available resource of the system is variable at different times. Numerical experimentation is conducted to evaluate the performance variability between two introduced models. The objective of this optimization problem is to minimize the total weighted completion time.

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Acknowledgments

This research has been supported by ANRT (Association Nationale de la Recherche et de la Technologie, France).

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Authors and Affiliations

  1. ICD, LOSI, Universite de Technologie de Troyes, UMR 6281, CNRS, 12 Rue Marie Curie, BP 2060, 10010, Troyes, France

    Nhan-Quy Nguyen, Farouk Yalaoui & Lionel Amodeo

  2. Opta-LP, 2 Rue Gustave Eiffel, 10430, Rosieres-pres-Troyes, France

    Hicham Chehade

  3. Park’nPlug, 13 Rue Marie Curie, 10430, Rosieres-pres-Troyes, France

    Pascal Toggenburger

Authors
  1. Nhan-Quy Nguyen
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  2. Farouk Yalaoui
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  3. Lionel Amodeo
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  4. Hicham Chehade
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  5. Pascal Toggenburger
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Corresponding author

Correspondence to Nhan-Quy Nguyen .

Editor information

Editors and Affiliations

  1. Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Wrocław University of Technology, Wrocław, Poland

    Bogdan Trawiński

  3. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

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Nguyen, NQ., Yalaoui, F., Amodeo, L., Chehade, H., Toggenburger, P. (2016). Solving a Malleable Jobs Scheduling Problem to Minimize Total Weighted Completion Times by Mixed Integer Linear Programming Models. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49390-8_28

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  • DOI: https://doi.org/10.1007/978-3-662-49390-8_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49389-2

  • Online ISBN: 978-3-662-49390-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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