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

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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.

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Author information

Correspondence to Mohammad Hassan Sebt.

Appendix: Nomenclatures

Appendix: Nomenclatures

The different index/sets, parameters, and variables in this paper are defined as follows:

See Table 3.

Table 3 .

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Alipouri, Y., Sebt, M.H., Ardeshir, A. et al. A mixed-integer linear programming model for solving fuzzy stochastic resource constrained project scheduling problem. Oper Res Int J 20, 197–217 (2020). https://doi.org/10.1007/s12351-017-0321-x

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Keywords

  • Combinatorial optimization
  • Fuzzy stochastic resource-constrained project scheduling problem
  • Fuzzy random variables
  • Mixed-integer linear programming