Nash bargaining and leader–follower models in water allocation: Application to the Zarrinehrud River basin,Iran

Mathematical models for conflict resolution are very important in integrated water resources and environmental management. This study proposes a new methodology to resolve conflicts among different water users and water suppliers while considering environmental requirements and the system’s constraints. A two-level leader–follower model is applied to maximize the net benefit with the Iran Water Resources Management Company as the leader and agricultural, domestic, and industrial users as followers subject to the system’s constraints. As a comparison, the Nash bargaining solution is also used to find a solution when simultaneous moves are assumed by the participants. The suggested method is then applied to the real case of the Zarrinehrud River basin that is one of the areas facing water shortages in Iran. For the actual optimization, Genetic Algorithm is used in order to avoid local optimum. As the contribution of this study, the results show that benefits for the leader in the leader–follower model increased in comparison with the Nash bargaining solutions.     

基于二层规划的流域水资源交易决策模型

对于一个流域而言,解决水资源短缺及污染最为有效的经济手段是建立以流域统一管理为基础,兼顾水权交易和排污权交易的市场体系.在水交易市场运作过程中存在着流域管理机构和具体用户之间的利益矛盾,为此本文构建了以流域管理机构作为流域水资源系统整体计划、控制和协调中心的上层决策者,各用户作为具有相对自主权的下层决策者的决策管理机制,并利用二层规划方法对流域水资源的交易进行建模研究,期望实现流域水资源的最优分配.最后,应用算例验证了模型及求解方法的可行性和有效性.     

A multi-objective optimal allocation model for irrigation water resources under multiple uncertainties

This paper proposed a multi-objective optimal water resources allocation model under multiple uncertainties. The proposed model integrated the chance-constrained programming, semi-infinite programming and integer programming into an interval linear programming. Then, the developed model is applied to irrigation water resources optimal allocation system in Minqin’s irrigation areas, Gansu Province, China. In this study, the irrigation areas’ economic benefits, social benefits and ecological benefits are regarded as the optimal objective functions. As a result, the optimal irrigation water resources allocation plans of different water types (surface water and groundwater) under different hydrological years (wet year, normal year and dry year) and probabilities are obtained. The proposed multi-objective model is unique by considering water-saving measures, irrigation water quality impact factors and the dynamic changes of groundwater exploitable quantity in the irrigation water resources optimal allocation system under uncertain environment. The obtained results are valuable for supporting the adjustment of the existing irrigation patterns and identify a desired water-allocation plan for irrigation under multiple uncertainties.     

Environmental flow requirements for integrated water resources allocation in the Yellow River Basin,China

Based on the classification and regionalization of the ecosystem, multiple ecological management objectives and the spatial variability of the environmental flow requirements of the Yellow River Basin were analyzed in this study. The summation rule was used to calculate water consumption requirements and the compatibility rule, i.e., “maximum” principle, was also adopted to estimate the non-consumptive use of water in the river basin. The environmental flow requirements for integrated water resources allocation were determined by identifying the natural and artificial water consumption in the Yellow River Basin. The results indicated that the annual minimum environmental flow requirements amounted to 317.62 × 10⁸ m³, which represented 54.76% of the natural river flows, while for the environmental flow requirements for the integrated water resources allocation were 262.47 × 10⁸ m³, which represented 45.25% of the natural river flows. The highest percentage of environmental flow requirements was 93.64% for the river ecosystem. It can be concluded that the primary concerns should be put on the downstream river water requirements to determine the environmental flows for integrated water resources allocation in a river basin.     

Optimal Base Station Positioning and Channel Assignment for 3G Mobile Networks by Integer Programming

In this paper, discrete mathematical programming approaches are used to solve the frequency allocation and cell site selection problem in an integrated setup. Both CDMA (code division multiple access) and FD/TDMA (frequency/time division multiple access) technologies will be important for 3rd generation mobile systems. If all users share the same bandwidth, base transmitter stations should be placed such that a maximum of traffic can be carried at low interference rates. The expected traffic is represented by spatially scattered weighted nodes. The problem to select an optimal set of base station locations from a given pool of configurations is formulated as an integer linear program and solved by combinatorial optimization methods. For systems which employ FD/TDMA schemes, the cell site optimization process depends on the assignment of channels. We suggest an integrated linear programming approach to solve both objectives in a single planning step. Because of the problems' tremendous complexity, special branch-and-bound procedures are developed as exact and approximate solution methods. An examples is given for a typical urban scenario with base transmitters below roof tops.     

THE ROLE OF ISSUE LINKAGE IN MANAGING NONCOOPERATING BASINS: THE CASE OF THE MEKONG

The Mekong River (MR) is the major water source in Southeast Asia, sharedby six countries. There is a rush, by riparian states, to acquire sources of alternative energy and other benefits to meet growing demands for water and energy. China and Myanmar have refused to cooperate fully in the MR Forum, leading to increase risks within the region. Development of the water resources of the MR Basin is the subject of intense debate both within the Mekong region and internationally. This paper investigates the concept of issue linkage to resolve unidirectional externalities in the MR. Using linked games, the paper shows that the downstream nations can consider the use of linkage as a form of side payment in achieving a basin‐wide agreement. While this approach supports the Integrated Water Resource Management‐based Basin Development Strategy adopted by the Mekong River Commission in April 2011 for managing the region's sustainability development, facts on the ground suggest that traditional issues to be linked may not be sufficient. The paper addresses this observation and suggests a cadre of issues, including nontraditional ones, to be analyzed in a future work.     

基于D-S证据理论的水资源合理配置方案综合评价

由于水资源合理配置具有多目标性、模糊性和不确定性的特点,其方案的综合评价可作为一个数据融合问题.利用改进的D-S证据理论合成公式,并考虑不同指标之间权重,给出了水资源合理配置方案综合评价模型.石羊河流域水资源配置方案评价的实例研究表明,D-S证据理论在水资源合理配置方案评价中有较好的实用性.     

Stochastic optimal design in multivariate stratified sampling

This work considers the allocation problem for multivariate stratified random sampling as a problem of integer non-linear stochastic multiobjective mathematical programming. With this goal in mind the asymptotic distribution of the vector of sample variances is studied. Two alternative approaches are suggested for solving the allocation problem for multivariate stratified random sampling. An example is presented by applying the different proposed techniques.     

Decentralization of responsibility for site decontamination projects: A budget allocation approach

A major problem currently confronting central governments is how to optimally allocate resources for decontamination of polluted sites. ‘Optimally’ here refers to obtaining maximum environmental benefits with the limited resources available. An important issue in budget allocation is that of decentralization, given the magnitude of the information flows between regional and central level necessary in a fully centralized approach. This paper investigates the use of mathematical programming models to support allocation procedures to obtain maximum environmental effectiveness and economic efficiency. We consider the situation where regional authorities provide limited, summary information to the central government, which then allocates budgets. The central government aims to maximize total environmental benefits, subject to a central budget constraint (and constraints on other resources). The problem can be formulated as a mixed integer programming problem, but the size of the problem precludes the search for optimal solutions. We present an effective heuristic and include computational results on its performance.     

The proportional solution for rights problems

Recently there have been several studies to provide axiomatic characterizations of solutions to rights problems. However, these studies do not give a satisfactory answer to the question why the proportional solution is the most widely used. This is the question addressed in this paper. To that purpose, we adopt the axiomatic approach; we suggest a set of axioms which a desirable solution should satisfy and we show that the proportional solution is the only solution to satisfy these axioms. Our main axioms are no advantageous reallocation and additivity. A solution satisfies no advantageous reallocation if no subgroup of claimants ever benefits by transferring parts of their claims between themselves. A solution satisfies additivity if it yields the same allocation whether the total estate is divided at once or in several steps.     

基于小波去噪和WNN-ARIMA组合模型的年径流预测

为解决单一的小波神经网络预测精度不高的问题,提出一种新的基于小波去噪和WNN-ARIMA组合模型,应用小波阈值去噪法对小波神经网络的输入值进行预处理,同时对模型残差值进行ARIMA模型修正.利用该组合模型对洮河流域下巴沟站年径流量进行预测,预测趋势和预测值与原始实测数据吻合度高,表明此组合模型可靠性强,可以有效预测年径...     

基于地理加权回归模型的塔里木河流域农业气候资源研究

以塔里木河流域农业气候资源为研究对象,通过收集该流域38个县市地区1995-2014年的气象、地理及经济方面的指标数据,运用R软件对其进行因子分析,得出年平均气温对该流域种植业具有明显的影响.然后,建立了地理加权回归模型,对收集的指标数据进行分析,研究该流域农业气候资源空间聚集与差异.结果表明:农业气候资源对塔河流域农业生产存在明显的空间影响.最后,为流域农作物的合理种植给出建议.     

A two-stage approach to multi-period allocation of savings among investment plans

This paper presents a two-stage multi-period decision model for allocation of the individual's savings into several investment plans. Although the U.S. economy is used as the background, the modelling methods are general enough to accommodate any tax law. The first stage of the model uses an asset-allocation method based on the single-index model. Because this method is static and does not provide for tax considerations and other constraints, it alone is not enough. The output of this optimal selection is used as exogenous parameters and controls for the second stage of the model which is an integer program. The IP includes fixed charges, statutory and budgetary constraints, a discount rate, and the risk level. We provide an example of this approach to illustrate how an individual can achieve his goals of terminal accumulations while maintaining the risk level, measured by the aggregate beta, he prefers. A linear programming relaxation of the IP model is utilized for sensitivity analysis to examine whether future adjustments in investment strategies are required. The model remains tractable enough for implementation by individuals who may not be experts in mathematical programming and financial planning.     

Mathematical programming approach to the Petri nets reachability problem

This paper focuses on the resolution of the reachability problem in Petri nets, using the mathematical programming paradigm. The proposed approach is based on an implicit traversal of the Petri net reachability graph. This is done by constructing a unique sequence of Steps that represents exactly the total behaviour of the net. We propose several formulations based on integer and/or binary linear programming, and the corresponding sets of adjustments to the particular class of problem considered. Our models are validated on a set of benchmarks and compared with standard approaches from IA and Petri nets community.     

Multi-goal analysis of a short-run reservoir operation

An application of multi-goal mathematical programming to a water resource management problem is described. This paper is concerned with the regulation of a reservoir which releases water to downstream users and has recreational activities located on its sides.The Pareto-optimal alternatives of the problem are found by an efficient search algorithm without applying the standard generating techniques of multi-goal programming. The application of the analysis to a real situation (a lake in Northern Italy) is given in detail.     

WAYFINDER: parallel virtual machine reallocation through A* search

Modern virtual machine (VM) management software enables consolidation of VMs for power savings or load-balancing for performance. While existing literature provides various methods for computing a better load-balanced, or consolidated goal state, it fails to adequately suggest the best path from the system’s current state to the desired goal allocation. This paper discusses an approach to efficient path finding in VM placement problems for cloud computing environments of moderate scale with results indicating the solution is reasonable for managing hundreds of VMs. We present an overview of known approaches to dynamic VM placement and discuss their shortcomings with respect to dynamic reallocation. We then describe a novel design and implementation of a heuristic search algorithm to determine optimal sequential migration plans to transition from a given VM-to-host allocation to an arbitrary desired allocation state. We then elaborate nuances of A* application to this domain along with our simulation-based validation approach. Finally, this work demonstrates a novel and highly effective technique for exploiting migration parallelism in order to rapidly achieving VM reallocation convergence suitable for continual workload rebalancing in cloud data centers.     

Minimum Cost Allocation of Tenders

In a big organization like the Australian Post Office, where large sums of money are spent to purchase a very large number of items every financial year, the problem is that of allocating the orders of the different items to the competing tenderers at a minimum cost. We have dealt with this in two sections; one is devoted to quantity discounts, the other to order value discounts. We have shown the mathematical formulation using integer and mixed integer linear programming, the mathematical programming systems used, the benefits gained and costs incurred, and the effects of the implementation of minimum cost allocation techniques on the organizational structure of some sections of the A.P.O. We have also shown that these techniques could be used to analyse the relative economic efficiencies of the competing tenderers with the objective of formulating a suitable economic purchasing policy for the organization concerned.     

A mathematical programming model applied to the study of water markets within the Spanish agricultural sector

Spanish irrigated agriculture uses about 80% of all the nation's available water resources. The need to increase the economic efficiency of current uses of water in the agricultural sector is perceived as the top priority of the country's national water policy. In Spain surface water is centrally allocated among competing users based on allocation criteria dictated by the Water Law. The complete absence of price or market signals is a major obstacle to induce irrigators to use water more efficiently. Water markets within the agricultural sector is a promising, though scarcely analyzed in Spain, solution to increase its economic efficiency. This research is an attempt to evaluate probable water transfers among farmers and irrigation districts as well as water price equilibria resulting from different water market arrangements. Three interconnected mathematical programming models permit the simulation of water use at the farm level and water market arrangements in the Guadalquivir Valley (Spain). Results show that water markets would be highly dependent on the level of transaction costs and on the relative reductions of water allotments due to nonoverlapping drought cycles among water districts.     

A multiobjective planning model for university resource allocation

Application of systematic approaches and dynamic planning for efficient resources allocation in institutions of higher education has been quite prevalent the past fifteen years. However, most models developed for university management have focused upon the analysis of input (budget/resource) requirements. They have generally neglected the existing environment, unique institutional values, and bureaucratic decision structures. In this study, a large scale goal programming model is developed for an efficient allocation of resources for an entire university for a five year planning period. The results of the model have been implemented in the form of administrative actions to achieve a set of multiple objectives.     

Uncertainty and value of information when allocating resources within and between healthcare programmes

A two-stage stochastic mathematical programming formulation has been developed to optimally allocate resources within and between healthcare programmes when there is an exogenous budget and the parameters of the healthcare models are variable and uncertain. This formulation solves the optimal resource allocation problem and calculates the expected value of acquiring additional information to resolve the uncertainties within the allocation. It is shown that the proposed formulation has several advantages over the chance constrained and robust mathematical programming methods.