Water Network Synthesis Using Mutation-Enhanced Particle Swarm Optimization

Different techniques for the synthesis of industrial water reuse/recycle networks have been developed in recent process integration research. These tools range from graphical pinch analysis approaches to mathematical programming models. The latter have the advantage of being flexible enough to incorporate various water network constraints, but in many cases these are often non-linear, thus making the identification of global optima difficult. Recent work has demonstrated the effectiveness of metaheuristic algorithms such as particle swarm optimization (PSO), for finding good solutions these problems. This work describes the use of a modified PSO for solving mixed integer non-linear programming (MINLP) models for water network synthesis. By incorporating a mutation operator for the binary variables in the model, the algorithm is able to escape sub-optimal network topologies and proceed towards better solutions than can be found with ordinary PSO. Two case studies involving water recycle/reuse are used to demonstrate the new design methodology.     

OPTIMAL WATER USE AND SALINITY CONTROL FOR ENERGY - UPPER COLORADO RIVER BASIN1

ABSTRACT: The Upper Colorado River Basin contains appreciable amounts of undeveloped fuel resources. Large quantities of oil shale, coal, and uranium have attracted recent economic and commercial interests. Development of these resources and subsequent conversion to alternative energy forms require an adequate supply of water. Water use for large scale energy development will place increasing demands on an already overstressed allocation of Colorado River water. Present water quality is at a concentration where increased salinity will result in economic detriments to holders of downstream water rights. The salt and water exchange in mining, processing, and spent fuel disposal processes has been incorporated as part of a two-level minimum cost linear programming algorithm. Mathematical simulation results provide an optimal use of Upper Colorado River water for levels of energy output such that salinity concentrations are maintained below predetermined levels.     

CAPITAL COST OF RURAL WATER DISTRIBUTION SYSTEMS1

ABSTRACT: The cost of water service to rural residents is very high compared to urban areas. This is true even after subsidization by Farmers Home Administration (FmHA) loans and grants. Capital cost data on 44 projects financed by the Ohio office of the FmHA during the period August 1968 to January 1977 are used to derive cost equations for 26 components of rural water distribution systems. These components represent 92 percent of the capital cost of the pipeline distribution systems studied. The data can be used to economically design rural water supply systems from a capital cost viewpoint. More data are needed on operation and maintenance costs as well as central and cluster well costs before totally economic system designs can be undertaken.     

ANALYZING THE IMPACT OF LAND USE ON SEWER SERVICE AREA PLANNING1

ABSTRACT: The density and distribution of land uses has important consequences for the planning of sewerage systems and for the costs of these systems. This paper examines these consequences using a simplified service area model. The model determines the area to be served by a central waste treatment plant, where alternative on-lot disposal systems are also available. The model is applied to various urban area configurations, which are summarized by their total populations and by their population density distributions. Both minimum regional cost and minimum local cost service area configurations are determined. In addition, the sensitivity of the model to the parameters of the cost and population density functions is assessed. It is found that the model is most sensitive to the parameters of the collection cost function.     

A CODED ALGORITHM FOR CAPACITY EXPANSION OF A WATER QUALITY MANAGEMENT SYSTEM1

ABSTRACT: This paper describes a mathematical model, an algorithm and a computer program that were specially developed to study the problem of a water quality management system undergoing a rapidly increasing environmental stress. The model output will determine the locations, sizes and the timing of construction of new treatment plants plus an overall treatment plant operating policy so that environmental standards are maintained at a minimum cost. The model, as formulated, is a 0-1 mixed integer programming problem which is solved by decomposing it into a capital budgeting problem (solved by Little's branch and bound algorithm) and an operational policy problem (solved by linear programming). The coded algorithm (in FORTRAN 10) has been tested with a semi-realistic example.     

A NONLINEAR MULTILEVEL MODEL FOR REGIONAL WATER RESOURCES PLANNING1

ABSTRACT: A nonlinear multilevel transportation model is developed to study large-scale allocations in a water resources system. The model uses a modified transportation matrix formulated with nonlinear cost functions as the basic subregional model and the goal coordination method for multilevel decomposition and optimization of the overall regional system. The model is applied to projected water requirements for Salt Lake County in 1985. Sources of water supply - surface water, ground water, import water, and reuse of reclaimed wastewater on a restricted basis - are available to satisfy water requirements for municipal, industrial, and agricultural sectors in four subregions. The conjugate gradient projection method is used to optimize the first level subregional models having cost functions of the form of C = aX^b, and the second level problem is solved using the conjugate gradient method.     

REGIONAL DETECTION OF CHANGE IN WATER QUALITY VARIABLES1

ABSTRACT: The detection of change in a hydrologic varaible, particularly water quality, is a current problem. A method is presented for testing whether there has been a shift in the mean of a hydrologic variable based on the well established bivariate normal distribution theory. In this technique, the dependent, or target, and the independent, or control, variables are formed as weighted linear combinations of the mean values at a number of locations in a selected target and control area. The weighting factors are determined based on a mathematical programming technique which minimizes the conditional coefficient of variation thereby minimizing the number of observations required to detect a change of a preselected magnitude in the mean of the target area. The result is a situation where a savings in the number of observations required to detect a change is a consequence of adding more stations: the space-time tradeoff. Two applications of the technique are presented, the first using electrical conductivity (EC) data from two sets of river basins and the second using EC data from a set of basins as the target variable and annual discharge as the control. The results indicate that a significant savings in time can be achieved by using this method.     

人工神经网络在水环境质量评价中的应用

为了将人工神经网络应用于水环境质量评价，应用了人工神经网络Ｂ—Ｐ算法，构造了水环境质量评价模型，该模型应用于实例评价结果表明，人工神经网络用于环境质量评价具有客观性，通用性和实用性。     

基于粒子群算法的城市垃圾中转站的空间布局研究

随着城市化的进程，垃圾处理设施成为影响城市化质量的重要指标。依据人们实际所关注的垃圾处理设施的总成本和负效应两个因素，在前人研究的基础上，建立了垃圾收运多目标模型，使得总成本和负效应最优化。根据模型设计了粒子群算法，该算法属于智能算法，且精度高，收敛快，在许多领域也得到广泛应用。用设计的粒子群算法并结合案例求出了Pareto最优解，给出三种决策方案，验证了模型和算法的有效性和可行性，为决策者提供了一种理论参考。