基于模糊多目标决策的城市水资源优化配置研究

针对城市用水系统的多水源、多用水户的特点,建立了城市水资源多目标分配模型.为对模型求解,首先计算各目标的模糊隶属度,将模型转化为模糊多目标决策模型,通过逐步缩小决策空间,最终得到模型的满意解.并以大连市为例,得到其2010、2020水平年的多水源多用水户的水资源配置结果.最后,分析了模糊多目标决策模型中各目标权重不同时对结果的影响.结果显示,该优化模型及模糊决策是合理可行的.     

多目标规划在邯郸水资源优化配置中的应用

多目标规划是进行水资源优化配置的一种重要方法，针对区域水资源优化配置中涉及多水源、多用途、不同供水区域的特点，根据多目标决策理论，以追求经济、社会、环境综合效益为主要目标对邯郸市水资源优化配置进行建模求解获得了较好的结果，可为地区水资源优化配置提供较为科学的依据。     

多目标规划在邯郸水资源优化调度中的应用

多目标规划是进行水资源优化调度的一种重要方法，针对区域水资源优化调度中涉及多水源、多用途、不同供水区域的特点，根据多目标决策理论，以追求经济、社会、环境综合效益为主要目标，对邯郸市水资源优化调度进行建模求解获得了较好的结果，可为地区水资源优化调度提供较科学的依据。     

丰台区水资源耦合配置模型研究

以丰台区水资源配置系统为研究对象,在分析供需水的基础上,构建双层优化模型,其中从环境角度体现对污染物排放量的严格控制,从经济角度体现区域水资源系统经济效益最大化。最终,体现区域水资源数量和质量的统一和不同需水部门之间的合理配置,并达到环境目标和经济目标的集成化。基于模糊满意度算法求解模型,模型结果表明:丰台区各规划水平年的供水量基本上可以满足各用户的需水要求,其中南水北调工程将在区域水资源配置系统中发挥重要作用。进一步地将双层规划模型和两个传统的单目标优化模型的结果进行对比分析,以期为不同决策者提供的规划方案。     

多目标规划法在南四湖流域水资源优化配置中的应用

水资源短缺及其水生态环境问题,已成为严重制约中国经济发展的重要因素。因此,如何对有限的水资源进行优化配置研究,已成为水资源规划与管理中的热点问题。该文运用多目标规划理论建立了一个考虑当地水、黄河水、长江水等多水源联合供水条件下的南四湖流域水资源优化配置模型。模型以经济和社会的综合效益最大为目标,确定了模型各参数,并调用Matlab优化工具箱中的函数进行编程求解,得到南四湖流域规划水平年(2015年)的水资源优化配置方案,为该流域水资源规划与管理提供了依据。     

多目标规划法在南四湖流域水资源优化配置中的应用

水资源短缺及其水生态环境问题,已成为严重制约中国经济发展的重要因素。因此,如何对有限的水资源进行优化配置研究,已成为水资源规划与管理中的热点问题。运用多目标规划理论建立了一个考虑当地水、黄河水、长江水等多水源联合供水条件下的南四湖流域水资源优化配置模型。模型以经济和社会的综合效益最大为目标,分析确定了模型各参数,并调用Matlab优化工具箱中的函数进行编程求解,得到南四湖流域规划水平年（2015年）的水资源优化配置方案,为该流域水资源规划与管理提供了依据。     

基于遗传算法的榆林水资源多目标优化配置(Ⅰ)

区域水资源优化配置是社会、经济及环境综合效益最佳的大系统多目标规划问题,根据榆林地区特点,基于区域水资源可持续利用理论,研究了以经济、社会和环境的综合效益最大为目标的优化配置模型建立的方法,讨论了基于遗传算法的多目标优化求解的可行性,为榆林地区及其他地区水资源多目标配置求解奠定了理论基础.     

区域水资源调度-分配迭代优化模型

在对水资源系统组成和结构分析的基础上,运用大系统优化理论建立了区域水资源系统多目标优化配置数学模型,包括水源优化调度、水量优化分配和调度分配迭代3个子模型。水源优化调度模型的求解采用轮库迭代方法和动态规划方法,水量优化分配模型的求解采用大系统分解协调中的D-W分解原理。对江苏省连云港市区水资源优化配置问题进行了研究,建立并求解了优化配置模型,结果表明,该市各区在2020规划水平年工业、农业、生活和环境部门都将出现不同程度的缺水情况。     

基于第二代非支配排序遗传算法(NSGA-Ⅱ)的水资源优化配置

水资源优化配置作为解决水资源短缺的重要手段,对于区域社会经济的可持续发展具有重要的意义。水资源优化配置模型是一个结构复杂的综合系统,传统的优化方法难以求得模型的全局最优解。第二代非支配排序遗传算法(NSGA-Ⅱ)是当前解决多目标优化问题最有效的方法之一,但在水资源优化配置领域应用很少。本文以浐灞河流域为例,尝试利用NSGA-Ⅱ优化方法求解该地区水资源多目标优化配置模型,研究了该方法在水资源优化配置模型求解中的适用性。结果表明:该方法得到的水资源优化配置结果合理、可行。     

基于粒子群算法的邯郸市水资源优化配置系统研究

随着经济的发展,邯郸市缺水矛盾日益严重,合理配置有限的水资源显得尤为重要。运用多目标规划理论建立一个多水源联合调度的水资源优化配置模型。该模型以经济、社会和环境的最大综合效益为目标,用粒子群算法求解,得到了邯郸市规划年（2020年）3种不同保证率下的水资源优化配置方案,为邯郸市的水资源规划和管理提供了依据。优化结果表明,粒子群算法在邯郸市水资源优化配置中是切实可行的。     

寺坪水电站优化调度模型

随着社会经济的快速发展,水资源供需矛盾日趋尖锐,如何合理调度有限的水资源已成为水资源管理中的现实而紧迫的任务。通过进一步研究水库调度的机理,采用非线性规划作为优化求解方法构建了水库优化调度模型,非线性规划结合了线性规划和动态规划各自的优点,并将水库调度中的各种因素融入数学模型中,较准确地计算模拟期间各种优化变量数值条件下的目标函数值,并比较得出最优值。之后,基于多目标思想,给出了一组Pareto前沿解集,通过寺坪水电站的应用,构建不同的目标函数,得到一系列决策方案,以便决策者选择偏好的决策方案。     

随机约束线性规划在水库综合利用中的应用

由于水库入流的不确定性，各用水目标的基本要求（目标放水量）将体现在年内各时期水库放水的随机约束上，配合水库线民生蓄泄水决策规则，将全部随机约束进行确定性等效转换，得到线性规划模型，经多次解析，就可得到水主加容量一定情况下的最优运行规则，针对大型水资源工程综合利用的多目标要求，研究建立了随机约束线性规划模型，以求解水库最优运行规划的方法，并以西南地区某大型综合利用水库为例，对模型进行求解，该方法随机     

Integrated Management of a Canal Command in a River Delta using Multi-Objective Techniques

Multi-criteria or multi-objective decision-making is becoming increasingly popular as a decision support tool for natural resource management.Stakeholders as well as the planners can be involved in the decision making process, using this approach. This article deals with the use of multi-criteria (multi-objective) technique in solving some complex problems related to water resource management. Five objectives were considered in the study. The benefit of combining these objective functions with the decisionsupport tool is that the management of land and water resourcescan be made more effectively. Based on this concept, a methodology was developed through this study, for the water managers and decision-makers, to obtain a compromising solutionin terms of area allocated under different crops and the magnitude of farming system variables in a canal command area. This study was under taken in the Mahanadi Delta of India. Multi-objective techniques such as Sequential Linear Fuzzy Programming and Goal Programming were used for their simplicity in computation and flexibility in application. Using Fuzzy programming technique, the objective function values under benefit maximization, production maximization, investmentminimization, labour maximization and labour minimizationwere found to be 44.26 M INR, 8795 tonnes, 42.00 M INR and548 150 man-days, respectively. These results were found tobe quite compromising in nature. Goal programming technique wasalso used to arrive at a consensus in allocation of the resources. It was used to decide the best out of the eight alternative priorities. Results indicated that only five alternative goals (Goal1, Goal2, Goal3, Goal6 and Goal8) had distinct allocations while the other three alternatives (Goal4,Goal5 and Goal7) had allocations similar to either of the abovefive alternatives irrespective of their priority levels. Croppingintensity was found to be the maximum (238%) for two of thegoals (Goal6 and Goal7). Though the results of the study were forthe specific site, the multi-criteria techniques used and therecommendations evolved are of objective nature and are applicable at any location for decision-making.     

基于动态规划法的多泥沙水源泵站优化调度研究

对多泥沙水源泵站的优化调度,主要以清水条件下算出的泵站稳态数据为基础,在一定的含沙率和下游所需流量下,运用泥沙公式求出泥沙水源条件下各种组合的水泵工作点;然后采用动态规划法,以抽取单位水量的耗能量最小作为目标函数,确定约束条件和递推方程,接着对模型求解,找出最优的开机组合。以某取水泵站为例进行了相关计算,计算结果表明:采用动态规划法,并运用相关的公式求出工作点;利用计算机语言,可以快速并准确地在满足条件下所有的水泵开机组合型式中寻找出最优的开机组合,以减少泵站的损耗,提高泵站的运行效率。借助于工程实例,对于含沙水流下泵站工作参数的推导、动态规划数学模型的建立以及调度目标函数的确定等过程进行了较为详细的介绍。     

Interval-parameter Two-stage Stochastic Semi-infinite Programming: Application to Water Resources Management under Uncertainty

In this study, an interval-parameter two-stage stochastic semi-infinite programming (ITSSP) method was developed for water resources management under uncertainty. As a new extension of mathematical programming methods, the developed ITSSP approach has advantages in uncertainty reflection and policy analysis. In order to better account for uncertainties, the ITSSP approach is expressed with discrete intervals, functional intervals and probability density functions. The ITSSP method integrates the two-stage stochastic programming (TSP), interval programming (IP) and semi-infinite programming (SIP) within a general optimization framework. The ITSSP has an infinite number of constraints because it uses functional intervals with time (t) being an independent variable. The different t values within the range [0, 90] lead to different constraints. At same time, ITSSP also includes probability distribution information. The ITSSP method can incorporate pre-defined water resource management policies directly into its optimization process to analyze various policy scenarios having different economic penalties when the promised amounts are not delivered. The model is applied to a water resource management system with three users and four periods (corresponding to winter, spring, summer and fall, respectively). Solutions of the ITSSP model provide desired water allocation patterns, which maximize both the system’s benefits and feasibility. The results indicate that reasonable interval solutions were generated for objective function values and decision variables, thus a number of decision alternatives can be generated under different levels of stream flow. The obtained solutions are useful for decision makers to obtain insight regarding the tradeoffs between environmental, economic and system reliability criteria.     

Two-Stage Interval-Parameter Stochastic Programming Model Based on Adaptive Water Resource Management

Water resource planning is often associated with system complexities and uncertainties, such as issues of precipitation randomness and complex the complexity of human social activities. In this study, a two-stage interval-parameter stochastic programming (TISP) model in conjunction with an adaptive water resource management (AWRM) model was applied. Compared to other optimization models, AWRM can address interactions between different water users and account for regional water exchange processes, and TISP models overcome the uncertainties of a water resource system by introducing interval-parameter and probability distribution methods. Reasonable solutions obtained by applying these models to a multi-water-resource, multi-region case show that in AWRM models, water can flow from a region of low efficiency to a region of high efficiency, improving water use efficiency. Under conditions of extreme scarcity, water can flow in the opposite direction thus ensuring regional minimum water requirements, enhancing system stability and reducing the probability of system paralysis. In policy making, optimistic water policies correspond to higher incomes but may be subject to higher risks of system failure. Alternatively, conservative policies are associated with a lower risk of system failure but easily waste water resources.     

并联输水管道设计方法

针对长距离并联输水系统的特点，以年费用最小为目标，应用动态规划建立了优化设计数学模型。对模型求解中涉及到的并联输水管管径的选定和流量分配问题作了探讨，推导了连接管设置间距计算式。算例表明，所设计的并联输水管道，可明显节省年费用。     

IFTSQP: An Inexact Optimization Model for Water Resources Management under Uncertainty

Abstract

An interval-fuzzy two-stage quadratic programming (IFTSQP) method is developed for water resources management under uncertainty. The methodincorporates techniques of interval-parameter programming, two-stage stochastic programming, and fuzzy quadratic programming within a general optimization framework to tackle multiple uncertainties presented as intervals, fuzzy sets and probability distributions. In the model formulation, multiple control variables are adopted to handle independent uncertainties in the model's right-hand sides; fuzzy quadratic terms are used in the objective function to minimize the variation in satisfaction degrees among the constraints. Moreover, the method can support the analysis of policy scenarios that are associated with economic penalties when the promised targets are violated. The developed method is then applied to a case study of water resources management planning. The results indicate that reasonable solutions have been obtained. They can help provide bases for identifying desired water-allocation plans with a maximized system benefit and a minimized constraint-violation risk.     

系统分析在衡水湖水资源规划管理中的应用

现代水资源水利工程通常是在多目标基础上进行规划、设计、施工、运行和扩建的。本文根据资源水利的治水思路和方略,运用系统规划理论,对衡水湖供水方案的选择、需水模型中水量在时间和行业上的最佳分配等做了大量计算。     

Optimal Operation of Reservoir Systems using Simulated Annealing

A stochastic search technique, simulated annealing (SA), is used to optimize the operation of multiple reservoirs. Seminal application of annealing technique in general to multi-period, multiple-reservoir systems, along with problem representation and selection of different parameter values used in the annealing algorithm for specific cases is discussed. The search technique is improved with the help of heuristic rules, problem-specific information and concepts from the field of evolutionary algorithms. The technique is tested for application to a benchmark problem of four-reservoir system previously solved using a linear programming formulation and its ability to replicate the global optimum solution is examined. The technique is also applied to a system of four hydropower generating reservoirs in Manitoba, Canada, to derive optimal operating rules. A limited version of this problem is solved using a mixed integer nonlinear programming and results are compared with those obtained using SA. A better objective function value is obtained using simulated annealing than the value from a mixed integer non-linear programming model developed for the same problem. Results obtained from these applications suggest that simulated annealing can be used for obtaining near-optimal solutions for multi-period reservoir operation problems that are computationally intractable.