Optimizing stochastic transportation networks with mixed constraints using pareto distribution

HIGHLIGHTS

• What: The authors propose a novel solution approach combining stochastic programming techniques with characteristics. More specifically, the authors focus on addressing the following key issues: Uncertainty in Supply and Demand: Traditional models often assume a fixed supply and demand, whereas real-world transportation systems face dynamic fluctuations in both, making it necessary to model uncertainty in a way that accounts for both typical variations and rare events. By integrating these elements, the authors aim to provide a more robust and realistic framework for optimizing transportation networks under uncertainty. The aim of this paper is to develop a . . .
  

   

  

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