Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Livelihoods,conflict and aid programming: is the evidence base good enough?

In conflict‐affected situations, aid‐funded livelihood interventions are often tasked with a dual imperative: to generate material welfare benefits and to contribute to peacebuilding outcomes. There may be some logic to such a transformative agenda, but does the reality square with the rhetoric? Through a review of the effectiveness of a range of livelihood promotion interventions—from job creation to microfinance—this paper finds that high quality empirical evidence is hard to come by in conflict‐affected situations. Many evaluations appear to conflate outputs with impacts and numerous studies fail to include adequate information on their methodologies and datasets, making it difficult to appraise the reliability of their conclusions. Given the primary purpose of this literature—to provide policy guidance on effective ways to promote livelihoods—this silence is particularly concerning. As such, there is a strong case to be made for a restrained and nuanced handling of such interventions in conflict‐affected settings.     

基于CALPUFF模型的漳州市大气环境容量研究

研究表明：CALPUFF模式是运用于广域的大气扩散模型,在区域范围较大的复杂地形条件下的应用具有突出的优势.利用CALPUFF大气扩散模型模拟漳州市2009年气象场和污染物浓度场,采用监测值对模拟结果进行验证表明模型的适用性;基于现状污染源,建立大气污染物传递系数矩阵,结合线性优化法测算了不同环境空气质量标准下漳州市大气环境容量.     

危险品运输网络优化设计研究综述

为分析当今反恐新形势下的危险品运输网络优化设计问题的研究现状,系统总结国内外关于一般场景和恐怖袭击威胁2种情况下危险品运输网络优化设计研究的主要模型和方法,梳理两者现有的研究内容,并讨论其共性及恐怖袭击威胁情景下的研究的新特点。结果发现:目前关于解决危险品运输网络优化设计问题模型的鲁棒性研究较为缺乏,尤其是模型在更为复杂和不确定性更强的恐怖袭击情景中适用性不强;危险品运输的鲁棒优化模型即使在突发事件条件下,也可以使决策者能够作出相对满意的决策;鲁棒性危险品运输网络能够规避风险扰动,可用来防止在恐怖袭击中因危险品车辆爆炸等造成更大的危害。     

海上应急保障资源调度的多目标模糊规划模型

针对现有应急资源调度模型无法完全适应海上应急保障环境的问题,建立了基于多目标模糊规划的海上应急资源调度模型.首先,将不确定的航行时间和资源需求量表示为三角模糊数,用时间隶属度函数的全积分对模糊应急开始时间进行确定化表示,用需求量隶属度表示需求点所接收的资源数量满足需求的程度.然后,考虑各需求点和各类资源的重要程度,以系统的时效性、需求满意度、安全性和经济性为优化目标建立多目标规划模型,最后,给出了模型的求解方法,并通过算例分析证明了方法的有效性.     

基于多目标优化的危险化学品运输模式探讨

近年来,危险化学品在运输过程中的事故越来越多,危害也越来越大,人们关于运输的安全意识也越来越强烈。本文介绍了多目标遗传算法、多目标优化、多目标进化以及他们之间的关系,并将多目标优化问题与危险化学品运输紧密联系起来,建立基于多目标优化的危险化学品运输模式。通过对危化品公路运输的问题描述以及约束条件（包括运输人员、押送人员、运输车辆、监督部门等等）的确定,把该问题转化成为拥有多目标的数学模型,最后利用网格法对危险化学品运输多目标优化进行求解,把多目标问题转化成为多个相互联系的2目标问题,通过减少目标函数边界的方法进行优化。通过这样求解的多目标问题,能够保证运输路径最短、费用最低、安全性最佳,为危险化学品运输安全提供技术支撑。     

A multi-agent simulation model for spatial optimisation of manure allocation

The EU Nitrate Directive has spurred many countries to regulate manure production and manure application. Farmers have three allocation options: spreading manure on their own land, transporting manure to other farmers' land or processing manure. The manure problem can be seen as an allocation problem. To better understand this allocation problem, we have developed the spatial mathematical programming multi-agent simulation (MP-MAS) model. This model has been applied in Flanders, Belgium, a region with a high concentration of livestock. The model evaluates the cost efficiency of policy intervention in the manure market through obliged processing. We propose to further optimise the policy using a regionally differentiated manure pressure indicator, which is directly derived from the dual outcome of the mathematical programme. This indicator increases transparency in the manure and processing market, leading to better decision support about location and type of manure processing.     

An Interval-Parameter Waste-Load-Allocation Model for River Water Quality Management Under Uncertainty

A simulation-based interval quadratic waste load allocation (IQWLA) model was developed for supporting river water quality management. A multi-segment simulation model was developed to generate water-quality transformation matrices and vectors under steady-state river flow conditions. The established matrices and vectors were then used to establish the water-quality constraints that were included in a water quality management model. Uncertainties associated with water quality parameters, cost functions, and environmental guidelines were described as intervals. The cost functions of wastewater treatment units were expressed in quadratic forms. A water-quality planning problem in the Changsha section of Xiangjiang River in China was used as a study case to demonstrate applicability of the proposed method. The study results demonstrated that IQWLA model could effectively communicate the interval-format uncertainties into optimization process, and generate inexact solutions that contain a spectrum of potential wastewater treatment options. Decision alternatives can be generated by adjusting different combinations of the decision variables within their solution intervals. The results are valuable for supporting local decision makers in generating cost-effective water quality management strategies.     

突发事件下城市群应急医疗床位共享建模

为给突发事件下城市群应急医疗床位共享提供理论依据,针对突发事件下城市群应急医疗床位共享问题,阐述突发事件下城市群应急医疗床位共享的必要性和可行性,并运用Multi-Hub理论,建立应急医疗床位在城市群集中的优化网络模型,并分析其内涵。在此基础上,采用基于层次分析法的线性回归方法,对多出救点、单个资源、多受灾点的应急医疗床位共享进行优化与讨论,并采用排队分配原则进行应急医疗床位具体去向的落实。研究结果表明:基于Multi-Hub理论的应急医疗床位区域集中优化模型与基于层次分析法的线性规划应急医疗床位调配优化模型,对突发事件下城市群应急医疗床位的共享具有优化和指导作用,能够提高突发事件下城市群应急医疗床位共享的效率,排队分配法能够在不超过医院容纳限度的前提下,保障应急救援的有序性和及时性。     

多目标规划在应急物流中的应用综述

为充分提高突发事件的应急救援效率,应急物流系统的建设至关重要。围绕应急物流系统,从应急物资管理、设施建立以及物流路径规划等方面入手开展相关研究工作的梳理和讨论,结果表明:目前相关研究受限于应急物流的应急体制建设不完善、多目标联系不紧密、信息化程度低、应急物资需求的动态性把握不准确等方面,而根据多目标规划方法提出的相应改进建议,能够实现救援线路最优化、救援时间最短化以及应急投入最小化等多个目标。