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A Multi-objective Genetic Algorithm for Optimization Time-Cost Trade-off Scheduling

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Knowledge Technology (KTW 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 295))

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Abstract

In this paper, we present a new genetic algorithm for Project Time-Cost Trade-off (TCTO) Scheduling problem. In the proposed GA, the selection of genes for mutation is adopted to be based on chromosome value, as solution convergence rate is high. This paper also offers a new multi attribute fitness function for the problem. This function can vary by DM preferences (time or cost). The algorithm is described and evaluated systematically. The computational outcomes validate the effectiveness of the suggested approach.

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Author information

Authors and Affiliations

  1. Iran University of Science and Technology, Tehran, Iran

    Hadi Aghassi

  2. Islamic Azad University of Arak, Arak, Iran

    Sedigheh Nader Abadi

  3. K.N. Toosi University of Technology, Tehran, Iran

    Emad Roghanian

Authors
  1. Hadi Aghassi
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  2. Sedigheh Nader Abadi
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  3. Emad Roghanian
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Editor information

Editors and Affiliations

  1. MIMOS Berhad, Knowledge Technology, Technology Park Malaysia, 57000, Kuala Lumpur, Malaysia

    Dickson Lukose

  2. Department of Systems and Network,College of Information Technology, Jalan IKRAM-UNITEN, Universiti Tenaga Nasional, 43000, Kajang, Malaysia

    Abdul Rahim Ahmad  & Azizah Suliman  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Aghassi, H., Nader Abadi, S., Roghanian, E. (2012). A Multi-objective Genetic Algorithm for Optimization Time-Cost Trade-off Scheduling. In: Lukose, D., Ahmad, A.R., Suliman, A. (eds) Knowledge Technology. KTW 2011. Communications in Computer and Information Science, vol 295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32826-8_38

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  • DOI: https://doi.org/10.1007/978-3-642-32826-8_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32825-1

  • Online ISBN: 978-3-642-32826-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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