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Research on Multi-stage Random Distribution Method

In: Liss 2020

Author

Listed:
  • Fachao Li

    (Hebei University of Science and Technology)

  • Yueye Zhang

    (Hebei University of Science and Technology)

  • Chenxia Jin

    (Hebei University of Science and Technology)

Abstract

With the rapid development of logistics, distribution as an important function, is increasingly concerned. Aiming at the problem of cost increase caused by a large number of delays in actual distribution, this paper proposes multi-stage distribution method based on stochastic programming. Firstly, we propose a multi-stage distribution model in a random environment. Based on the stochastic programming model with the lowest cost, the situation that the whole vehicle distribution requirements are not met in the distribution cycle is discussed. Due to the randomness of demand in distribution, the stochastic programming model will be transformed into the expected value model. Secondly, we simplify the multi-stage distribution model into a node decision-making model, and then use an algorithm to get the decision. Finally, combined with a case, the rationality of the model and the effectiveness of the algorithm are verified.

Suggested Citation

  • Fachao Li & Yueye Zhang & Chenxia Jin, 2021. "Research on Multi-stage Random Distribution Method," Springer Books, in: Shifeng Liu & Gábor Bohács & Xianliang Shi & Xiaopu Shang & Anqiang Huang (ed.), Liss 2020, pages 555-566, Springer.
    • Handle: RePEc:spr:sprchp:978-981-33-4359-7_39
    DOI: 10.1007/978-981-33-4359-7_39
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