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A Genetic Algorithm for Solving Fuzzy Resource-Constrained Project Scheduling

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3612))

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Abstract

This paper studies the resource-constrained project scheduling problem with fuzzy activity duration and fuzzy deadline. On the basis of the concept of schedule robustness for fuzzy deadline and fuzzy project makespan, we seek for a schedule that maximizes the schedule robustness. First, An efficient genetic algorithm (GA) based on activity list representation is proposed for solving this problem, the performance of our GA and GA based on the priority value representation is compared. Second, we study the impact for the two different weak comparison rules (integral value method, distance method) in the performance of GA. The computational experiment shows that the performance of the proposed GA is better than GA appearing in the literature, there is no significant difference between the two weak comparison rules on the Performance of the algorithm.

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Author information

Authors and Affiliations

  1. Department of Mathematics of the Science, Tianjin University, Tianjin, 300072, China

    Hong Wang & Dan Lin

  2. Institute of System Engineering, Tianjin University, Tianjin, 300072, China

    Hong Wang & Minqiang Li

Authors
  1. Hong Wang
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  2. Dan Lin
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  3. Minqiang Li
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Wang, H., Lin, D., Li, M. (2005). A Genetic Algorithm for Solving Fuzzy Resource-Constrained Project Scheduling. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_20

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  • DOI: https://doi.org/10.1007/11539902_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28320-1

  • Online ISBN: 978-3-540-31863-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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