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International Symposium on Neural Networks

ISNN 2009: Advances in Neural Networks – ISNN 2009 pp 60–69Cite as

Project Scheduling Problem for Software Development with Random Fuzzy Activity Duration Times

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5552))

Abstract

This paper presents a new method that describes activity duration times, which can be as random fuzzy variables to solve the software project scheduling problem. It solves the problem of the present classic models, such as PERT and CPM, which are weak in solving project scheduling problem for software development due to the concurrent, iterative and evolutionary nature characteristics of software projects. Next, a novel stochastic software project scheduling model —expected cost model —is suggested. Furthermore, basing on genetic algorithm and random fuzzy simulation, a hybrid intelligent algorithm is designed to solve the expected cost model. Numerical experiments illustrate the effectiveness of the hybrid intelligent algorithm.

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Author information

Authors and Affiliations

  1. State Key Lab of Software Engineering, WuHan University, WuHan, 430072, China

    Wei Huang, Lixin Ding, Bin Wen & Buqing Cao

  2. JiangXi Agricultural University, NanChang, 330045, China

    Wei Huang

Authors
  1. Wei Huang
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  2. Lixin Ding
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  3. Bin Wen
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  4. Buqing Cao
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático,, CINVESTAV-IPN,, A.P. 14-740, Av.IPN 2508,, D.F., 07360,, México, México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering,, Stevens Institute of Technology,, NJ 07030,, Hoboken,, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering,, South Dakota School of Mines & Technology,, 501 E. St. Joseph Street,, SD 57701,, Rapid City,, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Huang, W., Ding, L., Wen, B., Cao, B. (2009). Project Scheduling Problem for Software Development with Random Fuzzy Activity Duration Times. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_8

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  • DOI: https://doi.org/10.1007/978-3-642-01510-6_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01509-0

  • Online ISBN: 978-3-642-01510-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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