Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-II

Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-II into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by in-troduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated;this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions.

Design of Water Network with Multiple Contaminants and Zero Discharge

The paper presents a procedure to design water network. First of all, water reuse system, water regeneration reuse system (including regeneration recycle) and wastewater treatment system are designed separately. But the interaction between different parts demands that each part is designed iteratively to optimize the whole water network. Therefore, on the basis of the separated design a water netvrork superstructure including reuse, regeneration and wastewater treatment is established from the system engineering point of view. And a multi-objective adaptive simulated annealing genetic algorithm is adopted to simultaneously integrate the overall water netvrork to balance the economic and environmental effects. The algorithm overcomes the defect of local optimum of simulated annealing (SA), avoids the pre-maturation of genetic algorithm (GA) and finds a set of solutions (pareto front) in acceptable computer time. Prom the pareto front, a point with minimum fresh water consumption will be extended to zero discharge as our ultimate goal.

Optimization on Water Resource System Operation Policy during Drought

The mixed linear programming model is commonly recognized to be an effective means for searching optimal reservoir operation policy in water resources system. In this paper a multi-objective mixed integer linear programming model is set up to obtain the optimal operation policy of multi-reservoir water supply system during drought, which is able to consider the operation rule of reservoir-group system within longer-term successive drought periods, according to the basic connotation of indexes expressing the water-supply risk of reservoir during drought, that is, reliability, resilience and vulnerability of reservoir water supply, and mathematical programming principles. The model-solving procedures, particularly, the decomposition-adjustment algorithm, are proposed based on characteristics of the model structure. The principle of model-solving technique is to decompose the complex system into several smaller sub-systems on which some ease-solving mathematical models may be established. The objective of this optimization model aims at maximizing the reliability of water supply and minimizing the maximum water-shortage of single time-period within water- supply system during drought. The multi-objective mixed integer linear programming model and proposed solving procedures are applied to a case study of reservoir-group water-supply system in Huanghe-Huaihe River Basin, China. The desired water-shortage distribution within the system operation term and the maximum shortage of single time-period are achieved. The results of case study verifies that the lighter water-shortage distributed evenly among several time-periods can avoid the calamities resulted from severe water shortage concentrated on a few time-periods during drought.

Conjunctive Use of Engineering and Optimization in Water Distribution System Design

Water Distribution Systems (WDSs) design and operation are usually done on a case-by-case basis. Numerous models have been proposed in the literature to solve specific problems in this field. The implementation of these models to any real-world WDS optimization problem is left to the discretion of designers who lack the necessary tools that will guide them in the decision-making process for a given WDS design project. Practitioners are not always very familiar with optimization applied to water network design. This results in a quasi-exclusive use of engineering judgment when dealing with this issue. In order to support a decision process in this field, the present article suggests a step-by-step approach to solve the multi-objective design problem by using both engineering and optimization. A genetic algorithm is proposed as the optimization tool and the targeted objectives are: 1) to minimize the total cost (capital and operation), 2) to minimize the residence time of the water within the system and 3) to maximize a network reliability metric. The results of the case study show that preliminary analysis can significantly reduce decision variables and computational burden. Therefore, the approach will help network design practitioners to reduce optimization problems to a more manageable size.

Water Resource Allocation under Consideration of the National NIY Plan in Harbin, China

Water resource allocation （WRA） is a useful but complicated topic in water resource management. With the targets set out in the Plan of Newly Increasing Yield （NIY） of 10×1011 Jin （1 kg=2 Jin） from 2009 to 2020, the immediate question for the Songhua River Region （SHRR） is whether water is sufficient to support the required yield increase. Very few studies have considered to what degree this plan influences the solution of WRA and how to adapt. This paper used a multi-objective programming model for WRA across the Harbin region located in the SHRR in 2020 and 2030 （p=75%）. The Harbin region can be classified into four types of sub-regions according to WRA： Type I is Harbin city zone. With rapid urbanization, Harbin city zone has the highest risk of agricultural water shortage. Considering the severe situation, there is little space for Harbin city zone to reach the NIY goal. Type II is sub-regions including Wuchang, Shangzhi and Binxian. There are some agricultural water shortage risks in this type region. Because the water shortage is relatively small, it is possible to increase agricultural production through strengthening agricultural water-saving countermeasures and constructing water conservation facilities. Type III is sub-regions including Acheng, Hulan, Mulan and Fangzheng. In this type region, there may be a water shortage if the rate of urbanization accelerates. According to local conditions, it is needed to enhance water-saving countermeasures to increase agricultural production to a certain degree. Type IV is sub-regions including Shuangcheng, Bayan, Yilan, Yanshou and Tonghe. There are good water conditions for the extensive development of agriculture. Nevertheless, in order to ensure an increase in agricultural production, it is necessary to enhance the way in which water is utilized and consider soil resources. These results will help decision makers make a scientific NIY plan for the Harbin region for sustainable utilization of regional water resources and an increase in agricultural production.

Control of water contamination on side window of road vehicles by A-pillar section parameter optimization

The water contamination on the side windows of moving vehicles is a crucial issue in improving the driving safety and the comfort.In this paper,an effective optimization method is proposed to reduce the water contamination on the side windows of automobiles.The accuracy and the efficiency of the numerical simulation are improved by using the lattice Boltzmann method,and the Lagrangian particle tracking method.Optimized parameters are constructed on the basis of the occurrence of the water deposition on a vehicle’s side window.The water contamination area of the side window and the aerodynamic drag are considered simultaneously in the design process;these two factors are used to form the multi-objective optimization function in the genetic algorithm(GA)method.The approximate model,the boundary-seeded domain method,and the GA method are combined in this study to enhance the optimization efficiency.After optimization,the optimal parameters for the A-pillar section are determined by setting the boundary to an area of W=7.77 mm,L=1.27 mm and H=11.22 mm.The side window’s soiling area in the optimized model is reduced by 66.93%,and the aerodynamic drag is increased by 0.41%only,as compared with the original model.It is shown that the optimization method can effectively solve the water contamination problem of side windows.