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两个轴辐式网络协同建设的多层编码遗传算法

胡晶晶 黄有方

胡晶晶, 黄有方. 两个轴辐式网络协同建设的多层编码遗传算法[J]. 西南交通大学学报, 2020, 55(5): 971-979. doi: 10.3969/j.issn.0258-2724.20190893
引用本文: 胡晶晶, 黄有方. 两个轴辐式网络协同建设的多层编码遗传算法[J]. 西南交通大学学报, 2020, 55(5): 971-979. doi: 10.3969/j.issn.0258-2724.20190893
HU Jingjing, HUANG Youfang. Multi-layer Coded Genetic Algorithm with Collaborative Construction of Two Hub-and-Spoke Networks[J]. Journal of Southwest Jiaotong University, 2020, 55(5): 971-979. doi: 10.3969/j.issn.0258-2724.20190893
Citation: HU Jingjing, HUANG Youfang. Multi-layer Coded Genetic Algorithm with Collaborative Construction of Two Hub-and-Spoke Networks[J]. Journal of Southwest Jiaotong University, 2020, 55(5): 971-979. doi: 10.3969/j.issn.0258-2724.20190893

两个轴辐式网络协同建设的多层编码遗传算法

doi: 10.3969/j.issn.0258-2724.20190893
基金项目: 上海市科学技术委员会科技基金(15dz1100900);上海市科研计划专项(17DZ2280200)
详细信息
    作者简介:

    胡晶晶(1989—),女,博士研究生,研究方向为供应链智能分析,E-mail:jingjingnankai@sina.com

    通讯作者:

    黄有方(1959—),男,教授,博士生导师,博士,研究方向为物流信息系统、供应链智能分析与实现,E-mail:yhuang@shmtu.edu.cn

  • 中图分类号: U492.3;TP183

Multi-layer Coded Genetic Algorithm with Collaborative Construction of Two Hub-and-Spoke Networks

  • 摘要: 为了降低物流网络的建设成本投入,充分利用物流资源,提出轴辐式网络间的协同建设. 同时建设两个轴辐式物流网络,一个轴辐式网络为自己网络中的每一个枢纽从另一个轴辐式网络中选择一组协作枢纽,两个网络可以共同使用协作枢纽. 目标是使两个轴辐式网络的建设成本和它们之间的协作成本总和最小. 首先,运用混合整数规划模型描述所研究的问题;其次,根据问题的复杂度,设计了多层编码的遗传算法来解决问题,一条染色体分别表示了两个轴辐式网络;最后,在算例中进行了参数敏感性分析,分析参数对各部分成本和物流网络结构及协作枢纽的影响. 分析结果表明:在两个网络的协同建设中,一个网络中转移到另一个网络的流量大小对两个网络各自的网络结构和构建成本具有显著的影响;协同建设能够同时系统化地优化两个轴辐式网络,降低成本,整合物流资源.

     

  • 图 1  遗传算法设计框架

    Figure 1.  Genetic algorithm design framework

    图 2  编码和交叉方式

    Figure 2.  Genetic coding and crossover mode

    图 3  CN和TN的轴辐式网络结构($\alpha = 2.5{\text{%}} ,\;\beta = 2.5$

    Figure 3.  Hub-and-spoke network structure of CN and TN ($\alpha = 2.5{\text{%}} ,\;\beta = 2.5$)

    图 4  CN和TN的轴辐式网络结构($\alpha \!=\!15.0{\text{%}} ,\;\beta = 2.5$

    Figure 4.  Hub-and-spoke network structure of CN and TN ($\alpha = 15.0{\text{%}} ,\;\beta = 2.5$)

    图 5  CN和TN的网络节点重叠情况($\alpha = 2.5{\text{%}} ,\;\beta = 2.5$

    Figure 5.  Network nodes overlap of CN and TN ($\alpha = 2.5{\text{%}} ,\;\beta = 2.5$)

    图 6  CN和TN的网络节点重叠情况($\alpha = 15.0{\text{%}} ,\;\beta = 2.5$

    Figure 6.  Network nodes overlap of CN and TN ($\alpha = 15.0{\text{%}} ,\;\beta = 2.5$)

    图 7  遗传算法的收敛情况($\alpha = 15.0{\text{%}} ,\;\beta = 2.5$

    Figure 7.  Convergence of genetic algorithm ($\alpha = 15.0{\text{%}} ,\;\beta = 2.5$)

    图 8  CN成本随着参数 $\alpha $ 的变化趋势

    Figure 8.  Cost variation of CN with $\alpha $

    图 9  TN随着参数 $\alpha $ 的变化趋势

    Figure 9.  Cost variation of TN with $\alpha $

    图 10  CN和TN的协作成本随参数 $\alpha $ 的变化趋势

    Figure 10.  Cost variation of TN and CN with $\alpha $

    图 11  CN和TN的协作成本随参数 $\beta $ 的变化趋势

    Figure 11.  Collaboration cost variation of CN and TN with $\beta $

    表  1  参数 $\alpha $ 取值变化时CN和TN的枢纽选址和协作枢纽的计算结果

    Table  1.   Calculation results of hub location and collaboration hub of CN and TN with different values of $\alpha $

    $\alpha $/%CN的枢纽TN的枢纽协作枢纽
    2.510,26,46,49,77,80,104,115,119,129,141,171,183,206,211,219,223,249,251,253,299,301,304,313,318,322,330,349,372,388,396,404,405,426,440,450,468,473,491,49412,38,59,67,75,87,95,124,131,141{26,46,49},{119,141,171},{206,223,249},{119,171,183},{141,171,219},{223,249,253},{223,249,253},{372,396,404},{349,372,405},{396,404,405}
    5.01,21,37,52,56,61,100,101,118,124,131,154,168,181,195,209,214,228,232,242,255,258,276,285,294,318,330,347,348,358,374,387,404,410,433,454,458,459,479,49831,36,46,57,67,86,94,121,135,139{118,131,168},{100,101,195},{118,154,168},{131,168,181},{168,181,228},{232,255,258},{232,255,258},{348,374,387},{358,374,410},{374,387,404}
    10.09,30,33,52,79,87,102,127,133,144,152,180,186,191,202,205,213,230,255,262,266,287,293,296,326,329,337,350,355,359,372,386,397,417,440,441,443,461,476,49919,29,54,57,79,94,96,130,135,139{52,87,127},{79,102,152},{180,186,202},{180,186,202},{205,230,255},{230,255,262},{262,266,337},{372,386,397},{350,372,417},{372,386,397}
    15.06,20,47,50,66,80,89,104,113,127,155,156,167,171,185,220,221,229,235,253,275,282,298,299,306,325,341,342,357,373,384,394,398,411,426,434,437,452,468,49212,29,48,53,84,102,103,113,128,132{20,47,50},{80,104,156},{155,171,185},{167,171,185},{221,253,275},{253,275,325},{275,325,373},{342,357,398},{394,398,411},{384,394,411}
    20.09,24,40,55,77,80,82,102,114,128,145,151,165,182,193,204,210,211,225,240,241,258,266,284,286,304,311,320,357,363,369,379,389,403,406,418,448,471,474,4935,7,11,13,14,19,23,28,32 49{9,24,77},{9,77,82},{24,40,55},{24,40,55},{77,82,151},{40,77,82},{77,82,151},{145,151,204},{55,114,128},{145,151,204}
    下载: 导出CSV

    表  2  参数$\beta $ 取值变化时CN和TN的枢纽选址和协作枢纽的计算结果

    Table  2.   Calculation results of hub location and collaboration hub of CN and TN with different values of $\beta $

    $\beta $CN的枢纽TN的枢纽协作枢纽
    0.514,16,31,53,63,86,102,109,127,151,156,165,191,194,205,217,224,233,239,243,273,282,290,321,324,333,335,337,351,352,354,364,396,401,404,434,446,471,490,49815,32,42,54,65,82,91,116,132,141{16,31,53},{53,127,156},{127,151,191},{127,165,194},{165,194,224},{233,243,290},{233,243,290},{335,352,396},{354,401,404},{396,401,404}
    2.59,16,32,50,62,63,77,107,115,130,135,154,174,183,189,209,214,232,244,251,258,276,279,288,303,321,342,349,351,357,369,389,390,401,408,432,461,482,483,48811,34,36,52,67,91,94,121,130,131{16,32,50},{77,130,154},{107,115,174},{130,183,189},{130,183,189},{232,244,258},{232,244,258},{342,389,390},{389,390,408},{349,389,401}
    4.59,30,47,55,73,87,93,131,133,143,157,167,186,194,206,213,219,221,247,251,258,263,297,300,308,320,321,340,364,366,368,374,391,413,435,444,473,474,483,48919,32,48,66,71,95,106,126,134,136{47,87,131},{131,157,167},{143,186,194},{167,186,194},{221,247,258},{221,247,258},{247,263,368},{340,366,374},{366,374,413},{340,374,391}
    6.57,16,41,52,58,94,97,114,130,135,149,164,170,196,209,220,227,236,238,239,255,259,305,307,326,328,336,340,344,369,375,381,405,409,428,432,448,457,470,4869,36,37,69,70,75,94,123,135,143{16,41,52},{97,114,209},{130,149,170},{227,238,255},{164,170,196},{149,220,239},{227,238,255},{344,381,405},{340,405,409},{381,405,409}
    8.59,24,41,46,63,82,94,107,125,133,147,149,171,196,214,217,221,235,247,261,267,276,281,282,294,298,312,328,354,363,383,387,400,416,433,443,459,460,478,49313,29,51,60,64,86,98,121,137,147{41,46,63},{63,107,147},{149,214,235},{149,171,196},{125,171,196},{247,261,267},{247,261,267},{363,383,387},{363,383,387},{363,400,416}
    下载: 导出CSV

    表  3  参数$\alpha $$\beta $取值变化时各个成本的计算结果

    Table  3.   Calculation results of each cost with different values of $\alpha $ and $\beta $

    参数costCN/
    × 1012
    costTN/
    × 1011
    costCol/
    × 109
    costTotal/
    × 1012
    α 2.5% 5.40 5.01 2.26 5.900
    5.0% 5.72 4.80 4.46 6.210
    10.0% 5.52 4.88 8.93 0.009
    15.0% 5.86 4.75 13.40 6.340
    20.0% 6.00 −14.00 19.20 4.620
    β 0.5 5.66 5.00 4.39 6.160
    2.5 5.50 4.74 4.46 5.980
    4.5 5.50 4.92 4.65 6.000
    6.5 5.59 5.46 4.67 6.140
    8.5 5.44 5.06 4.85 5.950
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-09-19
  • 修回日期:  2019-12-11
  • 网络出版日期:  2019-12-15
  • 刊出日期:  2020-10-01

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