基于水资源高效利用的塔里木河流域农业种植结构优化研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
塔里木河流域地处我国西北内陆干旱地区,当前日趋紧张的水资源与持续恶化的生态环境已经成为制约流域社会经济可持续发展的瓶颈。流域农业用水比重约占总用水量的95%,严重挤占生态用水,且农业用水效率较低。因此,在保证流域粮食安全、生态安全和战略水安全的前提下,提高农业用水效率,减少农业用水量,成为解决流域农业用水与生态环境用水矛盾,缓解流域水资源紧缺与生态环境恶化局面的关键所在。本研究针对该流域农业用水效率偏低,种植结构不尽合理,耗用水量过大等问题,在对流域水资源、农业用水和种植业结构分析的基础上,建立基于水资源高效利用的农业种植结构多目标优化模型及其优化评价指标体系,并探讨流域农业种植结构优化宏观调控机制,以期为今后流域乃至干旱荒漠绿洲区农业种植结构规划和政策分析提供理论依据。
     1、通过对塔里木河流域相关水行政管理部门、基层技术人员及农户半结构访谈、问卷调查和现场勘察等方式,获得了流域种植结构、农业用水及生态环境等方面的基础数据、流域发展规划及其统计资料。调查结果表明:塔里木河流域粮、经、饲种植面积比例不够协调,饲料作物种植面积过小;高耗水作物种植面积偏大,水分生产效益较低;以往种植结构调整时对种植业的社会效益及其生态效益考虑不够,更未针对流域极度干旱的气候特点,从提高水分生产效益出发,建立基于水资源高效利用的农业种植结构。
     2、借鉴可持续发展理论、系统工程理论等种植业结构优化理论,以水资源高效利用为核心,以总净产值最大、粮食产量最大、生态效益最大及水分生产效益最大为目标,以耕地面积、可利用农业水资源量、社会需求、种植业净产值等5个方面的8个条件为约束,建立了基于水资源高效利用的塔里木河流域种植结构多目标优化模型。并选取流域重要的农牧业县—温宿县为例,采用能快速、直接求得全局非劣解集的粒子群算法对模型进行了求解。结果表明:通过作物种植结构的合理优化,在保证种植业总净产值、粮食总产量、生态效益及水分生产效益均得到一定程度提高的情况下,仍能获得比较显著的节水效益;2005年流域种植业灌溉用水总量为245.43亿m3,利用温宿县的优化计算成果,若不进行种植结构优化,预计流域2010年和2015年种植业灌溉水量分别需要241.25亿m3和225.49亿m3,而通过种植结构优化,种植业灌溉用水量可大幅消减,2005年实际只需要208.29亿m3,而2010年和2015年分别下降为192.60亿m3和181.29亿m3。节约的水资源量在满足快速增长的工业用水和生活用水需求的同时,也可为持续恶化的流域生态环境提供一定的生态环境用水量。
     3、作物种植结构优化调整的后效性评价是种植结构优化调整的重要组成部分,论文建立了由目标层、准则层、指标层3个层次所组成的评价指标体系。评价指标体系以流域种植结构优化合理度为目标层,设置了水资源利用高效性、社会公平性、经济合理性及生态安全性4个准则层,共计24项基础性指标。利用改进的层次分析法,采用MATLAB编程对建立的评价模型进行了求解。评价结果表明,通过作物种植结构优化,2005年、2010年和2015年优化后的种植结构合理程度分别较优化前提高了24.8%、23.2%和26.3%。因此,所采用的种植结构优化方案使种植业获得了一定的经济、社会和生态环境效益,并大大提高了水资源利用率和利用效率,证明种植结构优化结果是合理的、可行的。
     4、在分析塔里木河流域种植结构优化调整的阻碍因素,如农村土地生产经营分散、流域各行政区域存在用水利益冲突、农业用水水价低与用水户科技文化水平低下等基础上,提出只有探索并逐步建立健全市场与计划相结合机制、农业有机补偿与激励机制、农业科技投入机制、社会参与机制、土地流转机制以及以销定产等优化机制,才能保证农业种植结构优化调整方案的有效实施。
The Tarim Watershed is located in the inland arid regions of Northwest China. The water scarcity and continuing deterioration of ecology have recently become the main restricting factors to sustainable socio-economic development in this area. Agricultural water accounts for about 95% of total water consumption, which lead to a shortage of ecological water, and the water use efficiency was quite low. So, based on ensuring food security, ecological security and water security, increasing efficiency of agricultural water use and decreasing consumption of agricultural water became the key factors to solve conflict between agricultural and ecological water consumption and alleviate the water shortage and ecological deterioration in the basin. In this study, for important issues of low efficiency of agricultural water use, unreasonable planting structure and excessive water consumption, a multi-objective optimization model based on the high water utilization efficiency and its corresponding evaluation system were built by analyzing the water resources, agriculture water consumption and planting structures in Tarim watershed. The macro-control mechanism of agro-planting structures optimization was addressed to provide theoretical basis for planning and policy analysis of future agro-planting structures in the basin, even in the arid desert oasis area.
     1. Through semi-structure interview, questionnaire investigation and on-site investigation among water administrative departments, technicians and farmers, a large number of information and data such as planting structures, agricultural water consumption, environment, developing planning and statistical data in the basin were collected. The survey results showed that the panting ratio of grain, economic crops and forage crops lack of coordination. The forage crops cultivation proportion was too small and the cultivation area of high water consuming crops was too large and so the water production efficiency was too low. The social and ecological benefits were hardly considered, and the agricultural planting structures based on high efficient water resource utilization were not founded to counter the problems of the extremely dry climate and increase the water-use production.
     2. Draw on the theories of sustainable development, system engineering and crop planting structure optimization, taking high efficient water resource use as core aim, considering the largest net output, the heaviest food yield, the biggest ecological benefits and the highest water production, a multi-objective model based on high water use efficiency and planting structure optimization in Tarim watershed was built, in which eight constraint conditions were selected from five aspects such as farmland area, the amount of water resources useable for agriculture, social demand, the net output of planting industry. Taking Wensu, an important agricultural county in this basin, for example, the solution was got by using PSO (particle swarm optimization) method of the whole set non-inferior solution model. The results showed that optimizing the agricultural planting structure can still lead to high water-saving benefits, while the net output of planting industry, total grain yield, ecological efficiency and water use production were increased to some extent. The total amount of water consumption for planting industry was 24.543 billion cubic meters in 2005. According to the results of optimizing simulation of Wensu, if the planting structure was not optimized, the planting industry will consumpt 24.125 billion cubic meters water in 2010 and 22.549 billion cubic meters water in 2015. Otherwise, after optimization, the total water consumption amount for planting industry could be reduced to 20.829 billion cubic meters in 2005, 19.260 billion cubic meters in 2010 and 18.129 billion cubic meters in 2015. The saved water could not only meet the rapid growth in the water use for industry and daily life, but also provide some water for the ecology which are suffering continued deterioration in the basin.
     3. The benefits assessment was an important part for optimizing the planting structure. A 3-layer evaluation system was set up, including the target layer, rule layer and index layer. The target layer was the planting structures rationality. There are 4 aspects in rule layer, such as the high use efficiency of water resources, social equality, economic rationality and ecological security. The index layer contains 24 basic indexes. Using the methods of AHP (improved analytic hierarchy process) and MATLAB procedure to solve the evaluation model, the results showed that after the optimization for the planting structure, the rationality of planting structure increased by 24.8% in 2005, 23.2% in 2010 and 26.3% in 2015 respectively compared to those before. At the same time, by optimizing the planting structure, the economic, social and ecological benefits of the planting industry were increased to some extent, and the utilization efficiency of water resources was improved significantly. Tanking together, it was feasible to make planting structure optimized. The results of optimizing the planting structure were proved to be reasonable and feasible.
     4. Base on analyzing the obstacles for optimizing the planting structure in Tarim watershed, such as the dispersion of rural production, conflict among different administrative regions, low price of agricultural water and low literacy levels of local farmers, we proposed that if only gradually establishing and improving mechanism of plan and market combination, compensation and motivation for agriculture, sci-tech investment in agriculture, land transferring, social participation and optimal sale-order-production et al., the optimization of planting structure could be effectively implemented.
引文
1.胡军华.塔里木河流域水权适时控制及管理研究[D].南京:河海大学, 2007.
    2.高明杰.区域节水型种植结构优化研究[D].北京:中国农业科学院, 2005.
    3. Robin Naidoo, Takuya Iwamura. Global-scale mapping of economic benefits from agricultural lands: Implications for conservation priorities[J]. Biological Conservation, 2007, 140(11): 40-49.
    4. Isn, S., Miran, B. Farmers' attitudes toward crop planning in Turkey[J]. Journal of Applied Sciences, 2005, 5(8): 1489-1495.
    5. V.L. Versace, D. Ierodiaconou, F. Stagnitti, et al. Appraisal of random and systematic land cover transitions for regional water balance and revegetation strategies[J]. Agriculture, Ecosystems & Environment, 2008, 123(4): 328-336.
    6.张玉启,张文霞,陈国惠.种植制度调整与农民增收问题的调查分析和政策建议——以对豫东地区种植结构调整的调查为例[J].西南农业大学学报, 2003, 5(4): 55-59.
    7.梁书民.中国农业种植结构及演化的空间分布和原因分析[J].中国农业资源与区划, 2006, 27 (2): 29-34.
    8.赵雪雁.水资源约束下的河西走廊农业结构优化与调整研究[J].干旱区资源与环境, 2005, 19(4): 7-12.
    9.农业部发展计划司.农业结构战略性调整——理论、政策与实践[M].北京:中国农业出版社, 2003, 1-3.
    10. D. Leenhardt, J. -L. Trouvat, G. Gonzalès, et al. Estimating irrigation demand for water management on a regional scale I. ADEAUMIS, a simulation platform based on bio-decisional modelling and spatial information[J]. Agricultural Water Management, 2004, 68(8): 207-232.
    11. Sudheer R. Satti, Jennifer M. Jacobs. A GIS-based model to estimate the regionally distributed drought water demand[J]. Agricultural Water Management, 2004, 66: 1-13.
    12. Laxmi Narayan Sethi, Sudhindra N. Panda, Manoj K. Nayak. Optimal crop planning and water resources allocation in a coastal groundwater basin, Orissa, India[J]. Agricultural Water Management, 2006, 83(6): 209-220.
    13. C.C.Maji, Earl.O.Heady. Optimal reservoir mnanagement and crop planning under deterministic and stochastic inflows[J]. Journal of the American Water Resources Association, 1980, 16(3): 438-443.
    14.康绍忠,粟晓玲,沈清林,等.石羊河流域水资源利用与节水农业发展模式的战略思考[J].水资源与水工程学报, 2004, 15(4): 1-8.
    15.周惠成,彭慧,张弛.基于水资源合理利用的多目标农作物种植结构调整与评价[J].农业工程学报, 2007, 23(9): 45-49.
    16.刘登伟,封志明,方玉东.京津冀都市规划圈考虑作物需水成本的农业结构调整研究[J].农业工程学报, 2007, 23(7): 58-63.
    17.石玉林,卢良恕.中国农业需水与节水高效农业建设[M].北京:中国水利水电出版社, 2001.
    18.吴普特.制约我国农业高效用水发展的主导因素分析[J].水土保持研究, 2002, 9 (2): 1-3.
    19.屈宝香,周旭英,张华,等.黄淮海地区种植业结构调整与水资源关系研究[J].中国农业资源与区划, 2003, 24(5): 29-32.
    20. Per J. Agrell, Antonie Stam, Günther W. Fischer. Interactive multiobjective agro-ecological land use planning: The Bungoma region in Kenya European[J]. Journal of Operational Research, 2004, 158(10): 194-217.
    21. Weibo Zhou, Yubao Wang. Impacts of water resources use on ecological environment of irrigation districts in arid region of Northwest China[A]. Shaozhong Kang, Bill Davies, Lun Shan, et al. Water-saving agriculture and sustainable use of water and land resources[M]. Xi’an: Shaanxi Science and Technology Press, 2003, 887-892.
    22. Wenbin Wu, Ryosuke Shibasaki, Peng Yang, et al. Global-scale modelling of future changes in sown areas of major crops[J]. Ecological Modelling, 2007, 208(11): 378-390.
    23.章家恩,饶卫民.农业生态系统的服务功能与可持续利用对策探讨[J].生态学杂志, 2004, 23(4): 99-102.
    24.王玉宝,蔡明科,何武全.农业节水生态环境效益评价指标体系[J].中国农业大学学报, 2006, 11(4): 65-70.
    25. Gudbrand Lien, J. Brian Hardaker, Ola Flaten. Risk and economic sustainability of crop farming systems[J]. Agricultural Systems, 2007, 94(2): 541-552.
    26.秦向阳.区域种植结构调整原理方法及决策支持系统开发应用[D].北京:中国农业大学, 2002.
    27.张勃,李吉均.黑河绿洲农业自然资源空间组合与资源潜力研究[J].兰州大学学报, 2001, 37(4):101-109
    28.邓振镛,张强,韩永翔,等.甘肃省农业种植结构影响因素及调整原则探讨[J].干旱地区农业研究, 2006, 24(3):55-59.
    29.吴殿廷.区域经济学[M].北京:科学出版社, 2003.
    30.裴源生,赵勇,陆垂裕,等.经济生态系统广义水资源合理配置[M].郑州:黄河水利出版社, 2000, 1-156.
    31. Animesh Biswas, Bijay Baran Pal. Application of fuzzy goal programming technique to land use planning in agricultural system[J]. Omega, 2005, 33(5): 391-398.
    32. F.B. Victoria, J.S. Viegas Filho, L.S. Pereira, et al. Multi-scale modeling for water resources planning and management in rural basins. Agricultural Water Management, 2005, 77(8): 4-20.
    33. Itoh, T., Ishii, H. and Nanseki, T. "A model of crop planning under uncertainty in agricultural management," International Journal of Production Economics 2003, 81-82(11): 555-558.
    34. Tasuku, Toyonaga,Takesh Itoh, et al. A crop planning problem with fuzzy random profit coefficients[J]. Fuzzy Optimization and Decision Making, 2005, 4(1): 51-69.
    35. Itoh, T., Ishii, H. and Nanseki, T. A model of crop planning under uncertainty in agriculturalmanagement[J]. International Journal of Production Economics, 2003, 81-82(11): 555-558.
    36.陈守煜,马建琴,张振伟.作物种植结构多目标模糊优化模型与方法[J].大连理工大学学报, 2003, 43(1): 12-15.
    37.新疆维吾尔自治区人民政府,中华人民共和国水利部.塔里木河流域近期综合治理规划报告[R].北京:中国水利水电出版社, 2002: 1-39.
    38.邹建中,张惠臻,罗丽君,等.新疆环塔里木盆地经济圈与天山北坡经济带区域经济发展对比分析[J].新疆农垦经济, 2007(8): 11-15.
    39.樊自立,马英杰,季方,等.塔里木盆地水资源利用与绿洲演变及生态平衡[J].自然资源学报, 2001, 16(1): 22-27.
    40.甄霖,谢高地,杨丽,等.基于参与式社区评估法的泾河流域景观管理问题分析[J].水土保持研究. 2007, 17(3): 129-133.
    41.张志,朱清科,朱金兆,等.参与式农村评估(PRA)在流域景观格局研究中的应用——以晋西黄土区吉县蔡家川为例[J].中国水土保持科学, 2005: 3(1): 25-31.
    42. Catherine Allan, Allan Curtis. Participatory Rural Appraisal[J]. Natural Resource Management, 2002, 5(1): 28-34.
    43.王学雄,周琼.小流域参与式土地利用规划探讨[J].水土保持研究. 2006, 13(6): 295-297.
    44.李勉,崔灵周,李占斌.参与性农村调查(PRA)的产生发展与应用[J].水土保持科技情报. 2000, (3): 18-20.
    45. Goebel, A. Process, Perception and Powernotes from Participatory Research in a Zimbabwean Resettlement Area[J]. Development and Change, 1998, 29(2): 277–305.
    46. Mathew Kurian, T. Dietz, K.S. Murali. Rule Compliance in Participatory Watershed Management: Is it a Sufficient Guarantee of Sustainable Rural Livelihoods[J]. Conservation and Society, 2005, 3(1): 43 - 71.
    47. Budumuru Yoganand, Tesfa G. Gebremedhin. Participatory Watershed Management for Sustainable Rural Livelihoods in India [EB/OL]. http://218.246.35.10/edufullmirror/ economicsmirror /jingjixue14 /JJX18UrbanRuralandRegionalEconomics020(534).pdf, 2006-2-5/2008-2-15.
    48. Simon Adebo. Training Manual on Participatory Rural Appraisal [EB/OL]. http://218.246.35.10/ edu-fullmirrorH/Agriculturemirror/agriculturemir09 /NY09Livestock (1634). pdf, 2000-12-31/2008-3 -10.
    49. Adam G. Drucker, Simon Anderson. Economic Analysis of Animal Genetic Resources and the Use of Rural Appraisal Methods: Lessons from Southeast Mexico[J]. International Journal of Agricultural Sustainability, 2004, 2(2): 77-97.
    50.赵金,陈曦,包安明,等.塔里木河干流土地利用监测尺度分析[J].自然资源学报, 2007, 22(5): 824-830.
    51.邓铭江.塔里木河流域未来的水资源管理[J].中国水利, 2004, (17): 20-23.
    52.胡顺军,康绍忠,宋郁东,等.塔里木盆地潜水蒸发规律与计算方法研究[J].农业工程学报. 2004, 20(2): 49-53.
    53.郭选政,张惠文,韩丽青,等.关于高度重视与综合治理农田残膜污染的建议案[EB/OL]. http://222.82.236.187/showcontent.asp?Nclassid=118 &id=4105, 2007-1-5/2008-2-16.
    54.邓铭江.塔里木河下游应急输水的水生态环境响应[J].水科学进展, 2005, 16(4): 586-591.
    55.张春霞,苏时鹏.从系统论角度认识绿色经济的发展[J].中国生态农业学报, 2005, 13(1): 7-9.
    56.白华,韩文秀.复合系统及其协调的一般理论[J].运筹与管理, 2000, 9(3): 1-7.
    57.裴源生,赵勇,陆垂裕,等.经济生态系统广义水资源合理配置[M].郑州:黄河水利出版社, 2000.
    58.罗其友.北方早区农业资源可持续配置模型研究[J].干旱地区农业研究, 1999, 17 (1): 95-99.
    59.罗其友.21世纪节水农业持续推进的战略思考[J].农业技术经济, 1999, (3): 5-9.
    60.雷英杰,张善文,.李续武,等. MATLAB遗传算法工具箱及应用[M].西安:西安电子科技大学出版社, 2005.
    61.王顺久,张欣莉,倪长键,等.水资源优化配置原理与方法[M].北京:中国水利水电出版社, 2007.
    62.陈守煜.工程模糊集理论[M].北京:国防工业出版社, 1998.
    63.陈守煜.复杂水资源系统优化模糊识别理论与应用[M].吉林:吉林大学出版社, 2002.
    64.马建琴.区域农业水资源优化模糊集分析及其应用研究[D].大连:大连理工大学, 2003.
    65.林锉云,董加礼.多目标的优化的方法与理论[M].吉林:吉林教育出版社, 1992.
    66. ZadehL.A. Optimality and nonscalar-valued performance criteria [J]. IEEE Transaction Automatic Control,1963, 59-60.
    67. GeofrionA.M. Proper efficiency and the theory of vector optimization [J]. Journal of Mathematical Analysis and Application,1968, 41(3): 491-502.
    68.张勇德.智能多目标优化方法及其应用研究[D].沈阳:中国科学院沈阳自动化研究所, 2005.
    69. Chames A , Cooper. Management models and industrial applications of linear programming[M]. NewYork, John Wiley & Sons, 1961.
    70. Ben-Tal, Aharon. Characteirzation of pareto and lexicographic optimal solutions. Multiple Cirteria Decision Making Theory and Application. Lecture Notes in Economics and Mathematical Systems, Berlin: Springer-Verlag, 1980.
    71. Tseng C.H., and T.WLu. Minimax multiobjective optimization in structural Design[J]. Intenrational Jounral for Numerical Methods in Engineering, 1990, 30(4): 1213-1228.
    72. Holland J.H. Outline for a logical theory of adaptive systems[J]. Journal of the Association for Computing Machinery, 1962, (3): 297-314.
    73. Holland J.H. A new kind of turnpike theorem[J]. Bulletin of the American Mathematical Society, 1969: 297-314.
    74. Foguel LJ. Artificial intelligence through simulated evolution. John Wiley& Sons, 1966.
    75. Koza J.R. Genetic programming on the programming of computers by means of naturalselection[M]. MIT Press, 1992.
    76. Koza J. R. Genetic programming II, automatic discovery of reusable programs. MIT Press, 1994.
    77.刘勇,康立山,陈屏.非数值并行算法(第二册) [M].北京:科学出版社, 2003.
    78.陈国良,王煦法,庄镇泉,等.遗传算法的理论及其应用[M].北京:人民邮电出版社, 1996.
    79. Chames A, Cooper and Ferguson W.W.R.O. Optimal estimation of executive compensation by linear programming[J]. Management Science, l955, (1): 138-151.
    80.杨善学.解决多目标优化问题的几种进化算法[D].西安:西安电子科技大学, 2007.
    81. N .Srinivas and K. Deb. Multiobjective optimization using nondominated sorting in genetic algorithms. Evolutionary Computation,1995, (2): 221-248.
    82. K. Deb, S.Agrawal, S.Pratap, T.Meyarivan. Fast elitist nondominated sorting genetic algorithm for multi-objective optimization: NSGA-11. LNCS, 2000, 849-859.
    83. C. M. Fonseca, P. J. Fleming. Multiobjective optimization and multiple constraint handling with evolutionary algorithms-PartI: A Unified Formulation. IEEE Transactions on Systems, Man, & Cybernetics Part A: Systems & Humans,1998, 28: 26 -37.
    84. C. M. Fonseca, P. J. Fleming. Multiobjective genetic algorithms made easy: Selection, Shairng and Mating Restriction. In 1st IEE/IEEE International Conferencd on Genetic Algorithms in Engineering systems, Sheffield, 1995.
    85. J. Horn, N. Nafpliotis. Multiobjective optimization using the niched pareto genetic algorithm. Technical Report 93005, Illinois Genetic Algorithm Laboratory Dept.of General Engineering, Universith of Illinoisat Urbana-Champaign, Urbana, 1993.
    86. E. Zitzler, M. Laumanns, L. Thiele. SPEAII: Improving the strength pareto evolutionary algoirthm for multiobjective optimization, evolutionary methods for design, Opitmization and Control with A pplicationsto In dustiral Problems, John Wiley & Sons, 2001.
    87. C. M. Fonseca, P J. Fleming. Genetic Algorithms for Multi-objective Optimization:For mu la tion,D iscussionan dG eneralization.Pr oceedingso fth eF ifthI nternationalC onferenceon G e ne ticA lgorithms, 1993, 416-423
    88. C. M. Fonseca, P. J. Fleming An overiew of evolutionary algorithms in multiobjective optimization. Evolutionary Computation, 1995, 3(1): 1-16.
    89. H .Jeffrey. Handbook of evolutionary computation.Chap. Multicriterion Decision Making. Vol ⒈of Back et al, 1997.
    90. V .Veldhuizen, A .David, G .B Lamont. Multiobjective evolutionary algorithm research: A history and analysis. Technical Report T R-98-03, Department Technology, Air Force Institute of Technology, Ohio, 1998.
    91. C.A. Coefo. A comprehensive survey of evolutionary-based multi-obejective optimization technique[J]. Knowledge and Data Information Systems, 1999, 269-308.
    92. V. Veldhuizen, A. David. Multiobjective evolutionary algorithms: classifications, analyses, andnew innovations(D). A FITIDS/ENG/99-01, Air Force Insitute of Technology, Wright-Patters on AFB, 1999.
    93. E.Zitzler. Evolutionary algorithms for multiobjective optimization: Methods and applications(D). Zuirch, Federal Institute of Technology (ETH), 1999.
    94.门震宇,康立山,付朋辉,等.基于演化算法实现多目标优化的岛屿迁徙模型[J].小型微型计算机系统, 2004, 25 (2): 237-241.
    95.崔逊学,李淼.多目标协调进化算法研究[J].计算机学报, 2001, 24(9): 979-984.
    96.朱学军,陈彤.多个体参与交叉的Pareto多目标遗传算法[J].电子学报, 2001, 29(1): 106-109.
    97.曹先彬,李金龙,王煦法.基于生态协同的多目标优化研究[J].软件学报,2001, 12(4): 521-528.
    98. J.K ennedy,R .C .E berhart, Y. Shi. Swarm intelligence.San Francisco: Morgan Kaufmann Publishers, 2001.
    99. R. C. Eberhart, X. Hu. Human tremor analysis using particle swarm optimization. In Proceedings of the IEEE Congress on Evolutionary Computation, Piscataway, NJ: IEEE Service Center, Seoul, 1999: 1927-1930.
    100.R. C. Eberhart, Y. Shi. Particle swarm optimization: developments, applications and resources. In Proceedings of Congress on Evolutionary Computation, NJ: IEEE service center, Piscataway, Seoul, 2001: 81-86.
    101.C. A .Coello, M. S. Lechuga. MOPSO: A proposal for multiple objective particle swarn optimizations. Proceedings of the IEEE Congress on Evolutionary Computation (CEC2002), Honolulu, Hawaii, 2002.
    102.Colorni A , Dorigo M , Maniezzo V . Distributed optimization by ant colonies[A]. Proceedings of ECAL 91-European Conferenceon Aaificil~Life[C].Paris, France: 1991, 134-142.
    103.Dorigo M ,Maniezzo V,Colomi A.The ant system:optimizationby a colony of cooperating agents[J].IEEE Transactions on Sys—terns,Man&Cybernetics B, 1996, 26(2): 29-41.
    104.Hochbanm D S.Approximate Algorithms for NP Hard Problems[D].Boston,MA:PWS Publishing Company, 1997.
    105.Bullnheimer B. Ant Colony Optimimtion in Vehicle Routing[D].Vienna:University of Vienna, 1999.
    106.Jayaraman V K,Kulkarni B D,Karale S,et a1. Ant colonyframework for optimal design and scheduling of batch plants[J].Computemand Chemical Engineering, 2000, 24(8): 1901-1912.
    107.McMullen P R.An ant colony optimization approach to addressing a JIT sequencing problem with multiple objectives[J].Artificial Intelligence in Engineering, 2001, 15(3): 309-317.
    108.林锦,朱文兴.凸整数规划问题的混合蚁群算法[J].福州大学学报(自然科学版), 1999, 27(6): 5-9.
    109.何靖华,肖人彬,师汉民.蚂蚁算法在机构同构判定中的实现[J].模式识别与人工智能,2001, 14(4): 406-412.
    110.忻斌健,汪镭,吴启迪.蚂蚁算法的研究现状和应用及蚂蚁智能体的硬件实现[J].同济大学学报, 2002, 30(1): 82-87.
    111.R. C. Eberhart, J. Kennedy. A new optimizer using particle swarm theory. Proceedings of the Sixth Intenrational Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995, 39-43.
    112.张利彪,周春光,马铭,等.基于粒子群算法求解多目标优化问题[J].计算机研究与发展, 2004, 41(7): 1286-1291.
    113.X. Hu, R. C. Eberhart. Multiobjective optimization using dynamic neighborhood particle swarm optimization. In Porceedings of the IEEE World Congress on Computational Intelligence, Hawaii, 2002, 1666-1670.
    114.S.Mostaghim, J. Teich. Strategies for finding good local guideson multi-objective particles warm optimization. IEEES warm Intelligence Symposium, 2003, 26-33.
    115.Coello C., Pulido G., Lechunga M. Handling multiple objecitves with particle swarm optimziation. IEEE Transactions on Evoluitonary Computation, 2004, 8(3): 256-279.
    116.J.E. Alvarez-Benitez, R. M. Everson, J. E. Fieldsead. A MOPSO Algorithm Based Exclusively on Pareto Dominance Concepts, Evoluitonary Mult-Criterion Optimization. Third Intenrational Conference, Lecture Notes in computer Science, Mexico: Springer, 2005, 3410: 459-473.
    117.杨燕,靳蕃, Kamel M.微粒群优化算法研究现状及其进展[J].计算机工程, 2004, 30(21):
    3-9.
    118.安伟刚.多目标优化方法研究及其工程应用[D].西安:西北工业大学, 2005.
    119.Carlos A. A proposal for multiple objective Particle Swarm optimization[A]. Congress on Evolutionary computation [C], Piscateway, New Jersey, 2002, 1051-1056.
    120.Shi Y,Eberhart R. Parameter selection in particle swarm optimization[A]. Porc. 1998 Annu. Conf. Evolutionary Programming[C], San Diego, 1998, 591-600.
    121.王顺久,张欣莉,倪长键,等.水资源优化配置原理与方法[M].北京:中国水利水电出版社, 2007.
    122.Burke I C, Yonker C M, Parton W J, et al. Texture, climate, and cultivation effects on soil organic content in US grasslandsoils [J] .Soil Science Society of America Journal, 1989, 53: 800-805.
    123.Costanza R, d'Arge R, de Groot R, et al. The value of the world's ecosystem services and natural capital [J]. Nature, 1997, 387: 253-260.
    124.Lee C.S, Chang S.P. Interactive fuzzy optimization for an economic and environmental balance in a river system [J] .Water Research, 2005, 39(1): 221-231.
    125.De Wit C T, van Keulen H,Seligman N G, et al. Appli-cation of interactive multiple goal programming techniquesfor analysis and planning of regional agricultural develop-ment[J]. Agricultural Systems, 1988, 26 (3): 211-230 .
    126.CHEN Luo-nan, AIHARA K. Chaotic simulated annealing by a neural network model withtransient chaos[J]. Neural Networks, 1995, 8: 915-930.
    127.陈晓坤,陈明,沈菊琴.农业节水投资与效益分析方法初探[J].灌溉排水. 2001, 20(4): 51-55.
    128.王远,吴玉柏.几种主要节水灌溉技术的经济效益分析[J].水利经济. 2002, (6): 34-40.
    129.郑捷,周世峰,吴涤非.节水灌溉条件下作物的经济效益分析[J].排灌机械. 2005, 23 (3): 39-41.
    130.国家发展和改革委员会发展规划司.全国生态环境建设规划[EB/OL]. http://dp.cei.gov.cn/lszl/hjgh.htm. 2004-5-23.
    131.钱正英.中国水资源战略研究中几个问题的认识[J].河海大学学报. 2001, 29(3): 1-7.
    132.雷廷武,蔡甲冰,屈丽琴.农业节水与经济社会环境可持续发展[J].农业工程学报. 2003,19 (增刊): 136-139.
    133.刘恒,耿雷华,陈晓燕.区域水资源可持续利用评价指标体系的建立[J].水科学进展.2003, 14(3): 265-270.
    134.谭跃进,陈英武,易进先.系统工程原理[M].长沙:国防科技大学出版社, 1999.
    135.周维博,李佩成.干旱半干旱地域灌区水资源综合效益评价体系研究[J].自然资源学报. 2003, 18(2): 289-293.
    136.范庆莲.塔里木河流域生态环境建设分区及配置模式研究[D].北京:北京林业大学, 2003.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700