基于区间两阶段模糊可信性约束模型的灌区水资源配置
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摘要
针对灌区水资源配置系统中的复杂性和不确定性,以湖北省漳河灌区为例,构建区间两阶段模糊可信性约束规划模型,实现灌区各用水户间水资源优化配置。模型以系统经济收益最大为目标函数,引入模糊变量、离散区间和概率分布表征系统中的多重不确定性,设置可信性置信水平解决带有违规概率的模糊风险问题。求解模型得到多种情景下水量、灌溉面积优化配置结果以及系统收益,结果表明,模型可以有效处理配置系统的不确定性问题,反映系统收益与风险之间的权衡,实现灌区水资源高效配置。优化结果有助于灌区管理者协调各用水户的利益冲突,制定合理的决策方案。
Due to the rapid development of urbanization and industrialization,the consequent increasing conflict between limited water resources and increased water demands gradually led to unsustainability of water resources utilization in an irrigation district. Therefore,it is crucial to optimize the water allocation to alleviate water shortage and promote the sustainable development of irrigation district. Taking Zhanghe Irrigation District in Hubei Province as an example,an interval-parameter two-stage stochastic fuzzy credibility constrained programming was developed for optimal water allocation. In the model,the maximal system benefit was regarded as the objective function. To reflect the multiple uncertainties,fuzzy variables,discrete intervals and probability distributions were introduced into the model framework. To address the fuzzy risk problems associated with the violation constraints,fuzzy credibility constrained programming was integrated into the interval-parameter two-stage stochastic programming model.Meanwhile,several credibility significance levels were given to examine the system failure risk. Optimal allocation schemes were obtained in the combination of different credibility levels( λ),inflow levels and fuzzy membership levels( α). The results indicated that the water inflow was positively related to the water resources allocation and agricultural irrigation areas; water and irrigation area allocation to all divisions were increased with the decrease of credibility level, which resulted in system benefit's expansion coupled with high violation risk. When λ was 1. 0,the system benefit range was [0. 741,1. 147]billion CNY,and when λ was set as 0. 8,the system benefit reached [1. 026,1. 325] billion CNY; with the increase of the α level,the system fuzzy feature was weakened,consequently the upper limit of the system benefit was gradually decreased and the lower limit of the system benefit was increased conversely; and the proposed model preferred to avoid high violation risk rather than purse high economic benefit impractically to some extent. The corresponding optimal results were helpful for managers to coordinate the conflict-laden water use issues,formulate reasonable allocation schemes,and achieve efficient utilization of water resources. Compared with the other optimal allocation in Zhanghe Irrigation District,the research had advantages as following: multiple uncertainties were considered and represented by proper mathematical methods; the tradeoff of system benefit and violation risk was reflected; multiple allocation schemes were provided under different scenarios; several engineering and non-engineering measures were suggested for sustainable development of Zhanghe Irrigation District; the analysis method and the model framework can also be applied to other similar regions.
Due to the rapid development of urbanization and industrialization,the consequent increasing conflict between limited water resources and increased water demands gradually led to unsustainability of water resources utilization in an irrigation district. Therefore,it is crucial to optimize the water allocation to alleviate water shortage and promote the sustainable development of irrigation district. Taking Zhanghe Irrigation District in Hubei Province as an example,an interval-parameter two-stage stochastic fuzzy credibility constrained programming was developed for optimal water allocation. In the model,the maximal system benefit was regarded as the objective function. To reflect the multiple uncertainties,fuzzy variables,discrete intervals and probability distributions were introduced into the model framework. To address the fuzzy risk problems associated with the violation constraints,fuzzy credibility constrained programming was integrated into the interval-parameter two-stage stochastic programming model.Meanwhile,several credibility significance levels were given to examine the system failure risk. Optimal allocation schemes were obtained in the combination of different credibility levels( λ),inflow levels and fuzzy membership levels( α). The results indicated that the water inflow was positively related to the water resources allocation and agricultural irrigation areas; water and irrigation area allocation to all divisions were increased with the decrease of credibility level, which resulted in system benefit's expansion coupled with high violation risk. When λ was 1. 0,the system benefit range was [0. 741,1. 147]billion CNY,and when λ was set as 0. 8,the system benefit reached [1. 026,1. 325] billion CNY; with the increase of the α level,the system fuzzy feature was weakened,consequently the upper limit of the system benefit was gradually decreased and the lower limit of the system benefit was increased conversely; and the proposed model preferred to avoid high violation risk rather than purse high economic benefit impractically to some extent. The corresponding optimal results were helpful for managers to coordinate the conflict-laden water use issues,formulate reasonable allocation schemes,and achieve efficient utilization of water resources. Compared with the other optimal allocation in Zhanghe Irrigation District,the research had advantages as following: multiple uncertainties were considered and represented by proper mathematical methods; the tradeoff of system benefit and violation risk was reflected; multiple allocation schemes were provided under different scenarios; several engineering and non-engineering measures were suggested for sustainable development of Zhanghe Irrigation District; the analysis method and the model framework can also be applied to other similar regions.
引文
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[16]ZHANG C L,GUO P.A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty[J].Journal of Hydrology,2017,553:735-749.
[17]李茉.基于不确定性分析的农业水土资源多尺度优化配置方法与模型研究[D].北京:中国农业大学,2017.LI Mo.Methods and medels for agricultural water-land resources multi-scale optimal allocation based on uncertainty analysis[D].Beijing:China Agricultural University,2017.(in Chinese)
[18]LIU B D.Uncertainty theory[M].Beijing:Uncertainty Theory Laboratory,2012.
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[20]ZADEH L A.Fuzzy sets as a basis for a theory of possibility[J].Fuzzy Sets and Systems,1999,100(1):9-34.
[2]姜秋香,付强,朱长虹,等.基于多维临界调控理论的水资源优化配置研究进展[J].东北农业大学学报,2015,46(7):103-108.JIANG Qiuxiang,FU Qiang,ZHU Changhong,et al.Research progress of water resources optimal based on the theory of multidimensional critical regulation and control[J].Journal of Northeast Agricultural University,2015,46(7):103-108.(in Chinese)
[3]LI W,WANG B,XIE Y L,et al.An inexact mixed risk-aversion two-stage stochastic programming model for water resources management under uncertainty[J].Environmental Science and Pollution Research,2015,22(4):2964-2975.
[4]祝杰,陈森林,万飚,等.漳河水库多目标中长期优化调度研究[J].中国农村水利水电,2013(9):60-66.ZHU Jie,CHEN Senlin,WAN Biao,et al.The application of NSGA-Ⅱfor medium long-term multi-objective optimal scheduling in Zhanghe Reservoir[J].China Rural Water and Hydropower,2013(9):60-66.(in Chinese)
[5]罗伟伟.基于风险规避的供应链契约协调机制研究[D].武汉:武汉大学,2017.LUO Weiwei.The research on the supply chain coordination mechanism with risk aversion[D].Wuhan:Wuhan University,2017.(in Chinese)
[6]CHEN S,SHAO D G,TAN X,et al.An interval multistage classified model for regional inter-and intra-seasonal water management under uncertain and nonstationary condition[J].Agricultural Water Management,2017,191:98-112.
[7]李晨洋,张志鑫.基于区间两阶段模糊随机模型的灌区多水源优化配置[J].农业工程学报,2016,32(12):107-114.LI Chenyang,ZHANG Zhixin.Multi-water conjunctive optimal allocation based on interval-parameter two-stage fuzzy-stochastic programming[J].Transactions of the CSAE,2016,32(12):107-114.(in Chinese)
[8]顾文权,邵东国,黄显峰,等.水资源优化配置多目标风险分析方法研究[J].水利学报,2008,39(3):339-345.GU Wenquan,SHAO Dongguo,HUANG Xianfeng,et al.Multi-objective risk assessment on water resources optimal deployment[J].Journal of Hydraulic Engineering,2008,39(3):339-345.(in Chinese)
[9]HUANG G H,LOUCKS D P.An inexact two-stage stochastic programming model for water resources management under uncertainty[J].Civil Engineering and Environmental Systems,2000,17(2):95-118.
[10]LIN Q G,HUANG G H,BASS B,et al.IFTEM:an interval-fuzzy two-stage stochastic optimization model for regional energy systems planning under uncertainty[J].Energy Policy,2009,37(3):868-878.
[11]付银环,郭萍,方世奇,等.基于两阶段随机规划方法的灌区水资源优化配置[J].农业工程学报,2014,30(5):73-81.FU Yinhuan,GUO Ping,FANG Shiqi,et al.Optimal water resources planning based on interval-parameter two-stage stochastic programming[J].Transactions of the CSAE,2014,30(5):73-81.(in Chinese)
[12]ZHANG F,GUO S S,REN C F,et al.Integrated IMO-TSP and AHP method for regional water allocation under uncertainty[J].Journal of Water Resources Planning and Management,2018,144(6):04018025.
[13]FU Q,LI L Q,LI M,et al.An interval parameter conditional value-at-risk two-stage stochastic programming model for sustainable regional water allocation under different representative concentration pathways scenarios[J].Journal of Hydrology,2018,564:115-124.
[14]ZENG X T,LI Y P,HUANG W,et al.Two-stage credibility-constrained programming with Hurwicz criterion(TCP-CH)for planning water resources management[J].Engineering Applications of Artificial Intelligence,2014,35:164-175.
[15]张成龙,郭萍,赵建明.不确定条件下的区间两阶段模糊可信性约束规划配水模型研究[J].中国农村水利水电,2016(8):97-101.ZHANG Chenglong,GUO Ping,ZHAO Jianming.An interval two-stage stochastic fuzzy credibility constrained programming for optimal irrigation water allocation under uncertainty[J].China Rural Water and Hydropower,2016(8):97-101.(in Chinese)
[16]ZHANG C L,GUO P.A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty[J].Journal of Hydrology,2017,553:735-749.
[17]李茉.基于不确定性分析的农业水土资源多尺度优化配置方法与模型研究[D].北京:中国农业大学,2017.LI Mo.Methods and medels for agricultural water-land resources multi-scale optimal allocation based on uncertainty analysis[D].Beijing:China Agricultural University,2017.(in Chinese)
[18]LIU B D.Uncertainty theory[M].Beijing:Uncertainty Theory Laboratory,2012.
[19]HUANG G H,BAETZ B W,PATRR G G.A grey linear programming approach for municipal solid waste management planning under uncertainty[J].Civil Engineering Systems,1992,9(4):319-335.
[20]ZADEH L A.Fuzzy sets as a basis for a theory of possibility[J].Fuzzy Sets and Systems,1999,100(1):9-34.