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A mixed-integer linear programming model for solving fuzzy stochastic resource constrained project scheduling problem

Author

Listed:
  • Yagub Alipouri

    (Amirkabir University of Technology (Tehran Polytechnic))

  • Mohammad Hassan Sebt

    (Amirkabir University of Technology (Tehran Polytechnic))

  • Abdollah Ardeshir

    (Amirkabir University of Technology (Tehran Polytechnic))

  • Mohammad Hossein Fazel Zarandi

    (Amirkabir University of Technology (Tehran Polytechnic))

Abstract

This paper addresses resource-constrained project scheduling problem with mixed uncertainty of randomness and fuzziness (FS-RCPSP). The activity durations are considered to be fuzzy random variables. A resource flow network based mathematical model with fuzzy random variables is presented. Then, this model is transformed into a mixed-integer linear programming model with crisp variables. The CPLEX 12.6.0.1 solver in AIMMS (2014) is employed for applying the proposed model to solve 960 benchmark instances generated from the well-known sets J30 and J60 in PSPLIB. The computational results are encouraging and indicate the ability of the proposed model to handle the FS-RCPSP.

Suggested Citation

  • Yagub Alipouri & Mohammad Hassan Sebt & Abdollah Ardeshir & Mohammad Hossein Fazel Zarandi, 2020. "A mixed-integer linear programming model for solving fuzzy stochastic resource constrained project scheduling problem," Operational Research, Springer, vol. 20(1), pages 197-217, March.
    • Handle: RePEc:spr:operea:v:20:y:2020:i:1:d:10.1007_s12351-017-0321-x
    DOI: 10.1007/s12351-017-0321-x
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    References listed on IDEAS

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    Cited by:

    1. Pejman Peykani & Jafar Gheidar-Kheljani & Sheida Shahabadi & Seyyed Hassan Ghodsypour & Mojtaba Nouri, 2023. "A two-phase resource-constrained project scheduling approach for design and development of complex product systems," Operational Research, Springer, vol. 23(1), pages 1-25, March.

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