Most research papers of the site selection model, such Location-allocation, focus on the algorithm itself, while ignoring the influences of the city, as a complex geographic system which has uncertainties and will develop dynamically. Therefore, it’s quite possible that the results of such models will dissatisfy the new demands, or even be incompatible with the new situation after the utilities located have been put into service. Based on the GeoCA urban land use simulation model, this paper establishes a new dynamic Location-allocation model so that the selection result has characteristics of extension, forecast and sustainable development. Besides, all the sub models, e.g. the population forecasting model, of this dynamic site selection model are able to be optimized alone. Hence, this model has a highly flexibility and is competent for special region’s requirements.
WU Shao-Kun, LI Xia, Liu Xiao-Ping, Gong You-Fu
. GeoCA Based Dynamic Site Selection Model —Shenzhen City as a Case Study[J]. SCIENTIA GEOGRAPHICA SINICA, 2008
, 28(3)
: 314
-319
.
DOI: 10.13249/j.cnki.sgs.2008.03.314
[1] ESRI. ARC/INFO Help. What is Location-Allocation? [Z]. 2001.
[2] Hakimi S L. Optimum distributions of switching centers in a communication network and some related graph theoretic problems [J]. Operations Research, 1965, 13: 462~475.
[3] Church R. The regionally constrained p-median problem [J]. Geographical Analysis, 1990, 22: 22~32.
[4] Alan T Murray. Capacitated Service and Regional Constraints in Location-allocation Modeling [J]. Location Science, 1997, 5(2): 103~118.
[5] Dijin Gong, Mistsuo Gen. Hybrid Evolutionary Method for Capacitated Location-allocation Problem [J]. Computers ind. Engng, 1997, 33: 577-580.
[6] Vladimir Marianov, Daniel Serra. Hierarchical location-allocation models for congested systems [J]. European Journal of Operational Research, 2001, 135: 195-208.
[7] Lozano S, Guerrero F, Onieva L. Kononen maps for solving a class of location-allocation problems [J]. European Journal of Operational Research, 1998, 108: 106-17.
[8] Kuang-Han Hsieh, Fang-Chih Tien. Self-organizing feature maps for solving location-allocation problems with rectilinear distances [J]. Computers & Operations Research, 2004(31): 1017-1031.
[9] S. Salhi, M D H Gamal. A Genetic Algorithm Based Approach for the Uncapacitated Continuous Location–Allocation Problem [J]. Annals of Operations Research, 2003, 123: 203-222.
[10] 黎 夏, 叶嘉安. 遗传算法GIS结合进行空间优化决策的研究[J]. 地理学报, 2004, 59(5): 745~753.
[11] 刘 铸, 汪定伟. 社会考试考场选择的多目标优化模型[J]. 东北大学学报(自然科学版), 2004(8): 758~760.
[12] 张 潜, 高立群, 胡祥培. 集成化物流中的定位-配给问题的启发式算法[J]. 东北大学学报(自然科学版), 2004(7): 637~640.
[13] 蒋忠中, 汪定伟. B2C电子商务中配送中心选址优化的模型与算法[J]. 控制与决策, 2005(10): 1125~1128.
[14] ReVelle C S, Swain R W. Central facilities location. Geographic Analysis [J], 1970, 2: 30-42.
[15] Khumawala B M. An efficient algorithm for the p-median problem with maximum distance constraints [J]. Geographical Analysis, 1973, 5: 309-321.
[16] 黎 夏, 叶嘉安. 主成分分析与Cellular Automata在空间决策与城市模拟中的应用[J]. 中国科学D辑, 地球科学, 2001, 31(8): 683~690.
[17] 贾 华, 祝国瑞. 土地利用变化研究中的CA与灰色局势决策. 武汉测绘科技大学学报[J], 1998, (6): 165~169.
[18] 汤君友, 杨桂山. 试论元胞自动机模型与LUCC时空模拟[J]. 土壤, 2003, 35(6): 456~460.
[19] Wu Fulong. Calibration of stochastic cellular automata: the application to rural-urban land conversions [J]. Int. J. Geographical Information Science, 2002, 16(8): 795-818.
[20] 黎 夏, 叶嘉安. 基于神经网络的单元自动机CA及真实和优化的城市模拟[J]. 地理学报, 2002, 57(2): 159~166.
[21] 黎 夏, 叶嘉安. 知识发现及地理元胞自动机[J]. 中国科学D辑, 地球科学, 2004, 34(9): 865~872.
[22] 深圳市城市管理所. 关于我市垃圾转运站建设问题的情况汇报[Z]. 2004.
[23] 王爱民, 刘加林, 尹向东. 深圳市土地供给与经济增长关系研究[J]. 热带地理, 2005,25(1): 19~22.
