• Journal of Geo-information Science
  • Vol. 22, Issue 5, 1120 (2020)
Yulong CHEN1、1、2、2, Zhizhu LAI3、3, and Zheng WANG2、2、3、3、*
Author Affiliations
  • 1.河南大学 黄河文明与可持续发展研究中心暨黄河文明传承与现代文明建设河南省协同创新中心,开封 475001
  • 1Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng 475001, China
  • 2.河南大学环境与规划学院,开封 475004
  • 2College of Environment and Planning, Henan University, Kaifeng 475004, China
  • 3.华东师范大学地理信息科学教育部重点实验室,上海 200241
  • 3Key Laboratory of Geographical Information Science, Ministry of Education of China, East China Normal University, Shanghai 200241, China
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    DOI: 10.12082/dqxxkx.2020.190443 Cite this Article
    Yulong CHEN, Zhizhu LAI, Zheng WANG. Optimization of Rural Primary and Secondary School Location based on Traffic Network[J]. Journal of Geo-information Science, 2020, 22(5): 1120 Copy Citation Text show less
    Flow chart of improved multi-objective simulated annealing algorithm
    Fig. 1. Flow chart of improved multi-objective simulated annealing algorithm
    The 21-node network
    Fig. 2. The 21-node network
    Flow chart of facility location-network design system calculation process
    Fig. 3. Flow chart of facility location-network design system calculation process
    Operation interface of rural schools optimized layout system
    Fig. 4. Operation interface of rural schools optimized layout system
    Road network map containing potential roads
    Fig. 5. Road network map containing potential roads
    School locations results for scenario 1
    Fig. 6. School locations results for scenario 1
    School locations and road upgrade results for scenario 2
    Fig. 7. School locations and road upgrade results for scenario 2
    School locations, road upgrades and construction results for scenario 3
    Fig. 8. School locations, road upgrades and construction results for scenario 3
    The spatial distribution of students' time to school at each village for different scenarios
    Fig. 9. The spatial distribution of students' time to school at each village for different scenarios
    算法NNMGDSP平均时间/s
    平均值/个总和/个平均值标准方差平均值标准方差
    MOSA7216537.41246.30924.29639.1184.77
    NSGA-II15456276.30106.20726.30315.6568.62
    IMOSA22647130.6040.12525.14170.0459.53
    Table 1. Comparisons of performance indicators of three algorithms
    方案编号新建设施个数(p)设施选址位置旅行成本(第一目标值)设施建设成本(第二目标值)
    1111 642 335400 000
    21151 488 424450 000
    321,221 495 064800 000
    421,151 331 460850 000
    5215,211 315 524900 000
    6215,171 303 8021 000 000
    7315,17,211 130 9021 450 000
    831,15,211 158 5601 300 000
    931,11,221 379 6361 200 000
    1031,11,151 216 0321 250 000
    1139,15,171 121 4381 550 000
    1231,15,171 146 8381 400 000
    Table 2. Scheme and objective function value of Pareto optimal solution in scenario 1
    方案编号新建设施个数(p)设施选址位置旅行成本(第一目标值)建设成本(第二目标值)
    11151 295 687559 000
    21151 132 810787 155
    31151 068 135890 765
    41151 002 049991 840
    5115864 6301 271 470
    6115807 6181 431 305
    7215,171 000 3921 267 605
    8215,17855 6481 466 570
    9215,17742 1581 687 960
    10215,17713 8001 736 255
    11215,17655 7681 865 215
    12215,17622 9961 981 305
    13215,17610 7462 078 610
    14215,17593 2412 195 025
    15215,17553 7862 313 000
    1631,15,17857 8981 712 325
    1731,15,17750 3371 874 305
    1831,15,17692 3052 003 265
    1931,15,17580 2912 118 835
    2031,15,17548 5362 199 760
    2131,15,17536 2852 297 065
    2231,15,17508 4002 458 200
    Table 3. Scheme and objective function value of Pareto optimal solution in scenario 2
    方案编号新建设施个数(p)设施选址位置旅行成本(第一目标值)建设成本(第二目标值)
    1115969 0111 049 911
    2115909 9841 176 466
    3115797 9701 292 036
    4115764 3721 420 996
    5115752 1551 479 340
    6115720 4081 560 265
    7115689 7161 781 031
    8215,17861 9531 458 445
    9215,17805 0141 580 320
    10215,17717 8081 753 675
    11215,17650 2271 782 035
    12215,17567 6611 932 035
    13215,17549 2772 012 960
    14215,17521 3882 174 095
    15215,17506 3682 292 070
    16315,17,21897 5601 859 931
    17315,17,21736 4672 098 156
    18315,17,21646 6872 308 041
    19315,17,21522 4562 481 955
    20315,17,21515 0372 549 215
    21315,17,21400 2202 724 416
    22315,17,21372 3312 885 551
    Table 4. Scheme and objective function value of Pareto optimal solution in scenario 3
    Yulong CHEN, Zhizhu LAI, Zheng WANG. Optimization of Rural Primary and Secondary School Location based on Traffic Network[J]. Journal of Geo-information Science, 2020, 22(5): 1120
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