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中国工业与应用数学学会会刊
主管:中华人民共和国教育部
主办:西安交通大学
ISSN 1005-3085  CN 61-1269/O1

工程数学学报 ›› 2020, Vol. 37 ›› Issue (6): 664-672.doi: 10.3969/j.issn.1005-3085.2020.06.002

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地下物流系统网络数学模型构建

王玉学,   汪子强   

  1. 东北石油大学数学与统计学院,大庆  163318
  • 收稿日期:2018-06-07 接受日期:2018-12-26 出版日期:2020-12-15 发布日期:2021-02-15
  • 基金资助:
    东北石油大学引导性创新基金 (2018YDL-19).

Mathematical Modeling of Underground Logistics System

WANG Yu-xue,   WANG Zi-qiang   

  1. Faculty of Mathematics and Statistics, Northeast Petroleum University, Daqing 163318
  • Received:2018-06-07 Accepted:2018-12-26 Online:2020-12-15 Published:2021-02-15
  • Supported by:
    Guidance Innovation Foundation of Northeast Petroleum University (2018YDL-19).

摘要: 本文基于最优化理论,研究地下物流系统的数学模型构建问题.首先做出合理假设,在此基础上利用集合覆盖模型确定一级和二级节点的数量及位置.基于鲍摩-瓦尔夫模型,以总成本最小为目标函数确定各级节点之间的管道建设,Matlab编程遗传算法求解模型,得到最优路线.考虑到建设期间应满足实际交通需求递增的可能,依据运输量对节点进行模糊聚类,确定每个建设期的建设路线,行成动态的时序演进图.最后结合求解的过程和结果,进行总结分析.

关键词: 集合覆盖模型, 鲍摩-瓦尔夫模型, 遗传算法, 模糊聚类

Abstract: This paper studies the mathematical modeling of underground logistics system based on the theory of optimization. First, we introduce reasonable hypotheses. On this basis, we determine the number and location of the first and second level nodes by the set covering model. Based on the Baumol-Wolfe model, minimizing the total cost as the objective function determines the pipeline construction among the nodes at all levels, the Matlab programming genetic algorithm is used to solve the model, and to get the optimal path. Considering the situation of increasing actual traffic demand, we cluster nodes by traffic volume, confirm the construction route for each construction period, and establish a dynamic sequence evolution diagram. Finally, we summarize and analyze the process and results of the solution.

Key words: set covering model, Baumol-Wolfe model, genetic algorithm, fuzzy clustering

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