Multi-objective Optimisation Design of Water Distribution Systems:Comparison of Two Evolutionary Algorithms

In order to compare two advanced multi-objective evolutionary algorithms,a multi-objective water distribution problem is formulated in this paper.The multi-objective optimization has received more attention in the water distribution system design.On the one hand the cost of water distribution system including capital,operational,and maintenance cost is mostly concerned issue by the utilities all the time;on the other hand improving the performance of water distribution systems is of equivalent importance,which is often conflicting with the previous goal.Many performance metrics of water networks are developed in recent years,including total or maximum pressure deficit,resilience,inequity,probabilistic robustness,and risk measure.In this paper,a new resilience metric based on the energy analysis of water distribution systems is proposed.Two optimization objectives are comprised of capital cost and the new resilience index.A heuristic algorithm,speedconstrained multi-objective particle swarm optimization( SMPSO) extended on the basis of the multi-objective particle swarm algorithm,is introduced to compare with another state-of-the-art heuristic algorithm,NSGA-II.The solutions are evaluated by two metrics,namely spread and hypervolume.To illustrate the capability of SMPSO to efficiently identify good designs,two benchmark problems( two-loop network and Hanoi network) are employed.From several aspects the results demonstrate that SMPSO is a competitive and potential tool to tackle with the optimization problem of complex systems.

Robust Airfoil Optimization with Multi-objective Estimation of Distribution Algorithm

A transonic airfoil designed by means of classical point-optimization may result in its dramatically inferior performance under off-design conditions. To overcome this shortcoming, robust design is proposed to find out the optimal profile of an airfoil to maintain its performance in an uncertain environment. The robust airfoil optimization is aimed to minimize mean values and variances of drag coefficients while satisfying the lift and thickness constraints over a range of Mach numbers. A multi-objective estimation of distribution algorithm is applied to the robust airfoil optimization on the base of the RAE2822 benchmark airfoil. The shape of the airfoil is obtained through superposing ten Hick-Henne shape functions upon the benchmark airfoil. A set of design points is selected according to a uniform design table for aerodynamic evaluation. A Kriging model of drag coefficient is constructed with those points to reduce computing costs. Over the Mach range from 0.7 to 0.8, the airfoil generated by the robust optimization has a configuration characterized by supercritical airfoil with low drag coefficients. The small fluctuation in its drag coefficients means that the performance of the robust airfoil is insensitive to variation of Mach number.

Application of Ice Pigging in a Drinking Water Distribution System:Impacts on Pipes and Bulk Water Quality

Ice pigging is an emerging technique for pipe cleaning in drinking water distribution systems.However,substantial confusion and controversy exist on the potential impacts of ice pigging on bulk water quality.This study monitored the microstructural features and composition of sediments and microbial community structures in bulk water in eight multimaterial Chinese networks.Chloride concentration analysis demonstrated that separate cleaning of pipes with different materials in complex networks could mitigate the risk of losing ice pigs and degrading water quality.The microstructural and trace element characterization results showed that ice pigs would scarcely disturb the inner surfaces of long-used pipes.The bacterial richness and diversity of bulk water decreased significantly after ice pigging.Furthermore,correlations were established between pipe service age,temperature,and chloride and total iron concentrations,and the 15 most abundant taxa in bulk water,which could be used to guide practical ice pigging operations.

Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

Optimal Location and Sizing ofMulti-Resource Distributed Generator Based onMulti-Objective Artificial Bee Colony Algorithm

Distribution generation(DG)technology based on a variety of renewable energy technologies has developed rapidly.A large number of multi-type DG are connected to the distribution network(DN),resulting in a decline in the stability of DN operation.It is urgent to find a method that can effectively connect multi-energy DG to DN.photovoltaic(PV),wind power generation(WPG),fuel cell(FC),and micro gas turbine(MGT)are considered in this paper.A multi-objective optimization model was established based on the life cycle cost(LCC)of DG,voltage quality,voltage fluctuation,system network loss,power deviation of the tie-line,DG pollution emission index,and meteorological index weight of DN.Multi-objective artificial bee colony algorithm(MOABC)was used to determine the optimal location and capacity of the four kinds of DG access DN,and compared with the other three heuristic algorithms.Simulation tests based on IEEE 33 test node and IEEE 69 test node show that in IEEE 33 test node,the total voltage deviation,voltage fluctuation,and system network loss of DN decreased by 49.67%,7.47%and 48.12%,respectively,compared with that without DG configuration.In the IEEE 69 test node,the total voltage deviation,voltage fluctuation and system network loss of DN in the MOABC configuration scheme decreased by 54.98%,35.93%and 75.17%,respectively,compared with that without DG configuration,indicating that MOABC can reasonably plan the capacity and location of DG.Achieve the maximum trade-off between DG economy and DN operation stability.

Remaining oil distribution characteristics in an oil reservoir with ultra-high water-cut

An accurate mapping and understanding of remaining oil distribution is very important for water control and stabilize oil production of mature oilfields in ultra-high water-cut stage.Currently,the Tuo-21 Fault Block of the Shengtuo Oilfield has entered the stage of ultra-high water cut(97.2%).Poor adaptability of the well pattern,ineffective water injection cycle and low efficiency of engineering measures(such as workover,re-perforation and utilization of high-capacity pumps)are the significant problems in the ultra-high water-cut reservoir.In order to accurately describe the oil and water flow characteristics,relative permeability curves at high water injection multiple(injected pore volume)and a semiquantitative method is applied to perform fine reservoir simulation of the Sand group 3e7 in the Block.An accurate reservoir model is built and history matching is performed.The distribution characteristics of remaining oil in lateral and vertical directions are quantitatively simulated and analyzed.The results show that the numerical simulation considering relative permeability at high injection multiple can reflect truly the remaining oil distribution characteristics after water flooding in an ultrahigh water-cut stage.The distribution of remaining oil saturation can be mapped more accurately and quantitatively by using the‘four-points and five-types’classification method,providing a basis for potential tapping of various remaining oil types of oil reservoirs in late-stage of development with high water-cut.

Solving material distribution routing problem in mixed manufacturing systems with a hybrid multi-objective evolutionary algorithm

The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.

Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties

This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.

Optimal Location and Sizing of Distributed Generator via Improved Multi-Objective Particle Swarm Optimization in Active Distribution Network Considering Multi-Resource

In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.

Estimation of Distribution Algorithm with Multivariate <i>T</i>-Copulas for Multi-Objective Optimization

Estimation of distribution algorithms are a class of evolutionary optimization algorithms based on probability distribution model. In this article, a Pareto-based multi-objective estimation of distribution algorithm with multivariate T-copulas is proposed. The algorithm employs Pareto-based approach and multivariate T-copulas to construct probability distribution model. To estimate joint distribution of the selected solutions, the correlation matrix of T-copula is firstly estimated by estimating Kendall’s tau and using the relationship of Kendall’s tau and correlation matrix. After the correlation matrix is estimated, the degree of freedom of T-copula is estimated by using the maximum likelihood method. Afterwards, the Monte Carte simulation is used to generate new individuals. An archive with maximum capacity is used to maintain the non-dominated solutions. The Pareto optimal solutions are selected from the archive on the basis of the diversity of the solutions, and the crowding-distance measure is used for the diversity measurement. The archive gets updated with the inclusion of the non-dominated solutions from the combined population and current archive, and the archive which exceeds the maximum capacity is cut using the diversity consideration. The proposed algorithm is applied to some well-known benchmark. The relative experimental results show that the algorithm has better performance and is effective.

Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.

Application of Dynamic Programming Method in Optimization of Water Distribution Pipe Network

With a water-supply network by dynamic programming. The minimal as an example, the network was optimized annual discounted costs were taken as an objective function and node pressure etc. as constraint conditions. The alternative pipe diameters were optimized as per enumeration method and the group allowing objective function with the least values would be the optimized one. It is proved the optimized pipe network reduced by 11.49% in terms of cost and the optimized ben- efits proved much significant.

STUDY ON OPTIMAL CONTROL OF MUNICIPAL WATER DISTRIBUTION NETWORK

A systematic investigation is made on the problems which are related to the optimal control of the municipal water distribution network.A mathematical model of forecasting the water short term demand is proposed using the time series trigonometric function analysis method;the service discharge based macroscopic model of network performance is established using the network structuring method;a relatively satisfactory mathematical model for the optimal control of water distribution network is put forward in view of security and economy,and solved by the constrained mixed discrete variable complex arithmetic.The model is applied in many examples and the results are satisfactory.

Effects on Sucrose Metabolism,Dry Matter Distribution and Fruit Quality of Tomato Under Water Deficit

Four irrigation treatments were designed with 2,4,6 and 8 d intervals to irrigate, respectively. Watering was stopped when the reading of the moisture tension sensor reached zero. The results indicated that glucose and fructose content of tomato's fruit were increased but sucrose content was decreased with fruit growth and development. In different stages, carbohydrate content of tomato fruit in the treatment 3 was the highest, in the treatment 2 was higher, and in the other treatments was the lowest. SS(sucrose synthase)activity was decreased but SPS(sucrose phosphate synthase)activity was increased with development of tomato. SS and SPS activity were increased but acid invertase and neutral invertase activity of ripe stage were decreased under deficit irrigation. Glucose and fructose content were increased in leaves of tomato under water deficit. Soluble sugars, organic acid and the ratio of sugar/acid in tomato fruits were increased and dry matter accumulation of plant was enhanced under water deficit. But the growth of fruits upside the plant and its dry matter accumulation were badly affected under water stress.

Modeling of residual chlorine in water distribution system

Water quality within water distribution system may vary with both location and time. Water quality models are used to predict the spatial and temporal variation of water quality throughout water system. A model of residual chlorine decay in water pipe has been developed, given the consumption of chlorine in reactions with chemicals in bulk water, bio films on pipe wall, in corrosion process, and the mass transport of chlorine from bulk water to pipe wall. Analytical methods of the flow path from water sources to the observed point and the water age of every observed node were proposed. Model is used to predict the decay of residual chlorine in an actual distribution system. Good agreement between calculated and measured values was obtained.

Temporal and spatial distribution characteristics of water resources in Guangdong Province based on a cloud model

With a focus on the difficulty of quantitatively describing the degree of nonuniformity of temporal and spatial distributions of water resources, quantitative research was carried out on the temporal and spatial distribution characteristics of water resources in Guangdong Province from 1956 to 2000 based on a cloud model. The spatial variation of the temporal distribution characteristics and the temporal variation of the spatial distribution characteristics were both analyzed. In addition, the relationships between the numerical characteristics of the cloud model of temporal and spatial distributions of water resources and precipitation were also studied. The results show that, using a cloud model, it is possible to intuitively describe the temporal and spatial distribution characteristics of water resources in cloud images. Water resources in Guangdong Province and their temporal and spatial distribution characteristics are differentiated by their geographic locations. Downstream and coastal areas have a larger amount of water resources with greater uniformity and stronger stability in terms of temporal distribution. Regions with more precipitation possess larger amounts of water resources, and years with more precipitation show greater nonuniformity in the spatial distribution of water resources. The correlation between the nonuniformity of the temporal distribution and local precipitation is small, and no correlation is found between the stability of the nonuniformity of the temporal and spatial distributions of water resources and precipitation. The amount of water resources in Guangdong Province shows an increasing trend from 1956 to 2000, the nonuniformity of the spatial distribution of water resources declines, and the stability of the nonuniformity of the spatial distribution of water resources is enhanced.

Interactions between wind and water erosion change sediment yield and particle distribution under simulated conditions

Wind and water erosion are among the most important causes of soil loss, and understanding their interactions is important for estimating soil quality and environmental impacts in regions where both types of erosion occur. We used a wind tunnel and simulated rainfall to study sediment yield, particle-size distribution and the fractal dimension of the sediment particles under wind and water erosion. The experiment was conducted with wind ero- sion firstly and water erosion thereafter, under three wind speeds （0, 11 and 14 m/s） and three rainfall intensities （60, 80 and 100 ram/h）. The results showed that the sediment yield was positively correlated with wind speed and rain- fall intensity （P〈0.01）. Wind erosion exacerbated water erosion and increased sediment yield by 7.25%-38.97% relative to the absence of wind erosion. Wind erosion changed the sediment particle distribution by influencing the micro-topography of the sloping land surface. The clay, silt and sand contents of eroded sediment were also posi- tively correlated with wind speed and rainfall intensity （P〈0.01）. Wind erosion increased clay and silt contents by 0.35%-19.60% and 5.80%-21.10%, respectively, and decreased sand content by 2.40%-8.33%, relative to the absence of wind erosion. The effect of wind erosion on sediment particles became weaker with increasing rainfall intensities, which was consistent with the variation in sediment yield. However, particle-size distribution was not closely correlated with sediment yield （P〉0.05）. The fractal dimension of the sediment particles was significantly different under different intensities of water erosion （P〈0.05）, but no significant difference was found under wind and water erosion. The findings reported in this study implicated that both water and wind erosion should be controlled to reduce their intensifying effects, and the controlling of wind erosion could significantly reduce water erosion in this wind-water erosion crisscross region.

Spatial distribution of soil moisture,salinity and organic matter in Manas River watershed,Xinjiang,China

With the classical statistical and geostatistical methods, the study of the spatial distribution and its in- fluence factors of soil water, salinity and organic matter was carried out for 0-70 cm soil layers in Manas River watershed. The results showed that the soil moisture data from all soil layers exhibited a normal distribution, with average values of 14.08%-21.55%. Geostatistical analysis revealed that the content of soil moisture had a moder- ate spatial autocorrelation with the ratios of nugget/sill ranging from 0.500 to 0.718, which implies that the spatial pattern of soil moisture is influenced by the combined effects of structural factors and random factors. Remarkable spatial distributions with stripped and mottled features were found for soil moisture in all different soil layers. The landform and crop planting had a relatively big influence on the spatial distribution of soil moisture; total soil salinity was high in east but low in west, and non-salinized soil and lightly salinized soil appeared at the northwest and southwest of the study area. Under the effect of reservoir leakage, the heavily salinized soils are widely distributed in the middle of the study area. The areas of the non-salinized and lightly salinized soils decreased gradually with soil depth increment, which is contrary to the case for saline soils that reached a maximum of 245.67 km2 at the layer of 50-70 cm. The types of soil salinization in Manas River watershed were classified into four classes： the sulfate, chloride-sulfate, sulfate-chloride and chloride. The sulfate salinized soil is most widely distributed in the surface layer. The areas of chloride-sulfate, sulfate-chloride, and chloride salinized soils increased gradually along with the increment of soil depth; the variation range of the average values of soil organic matter content was be- tween 7.48%-11.33%. The ratios of nugget/sill reduced gradually from 0.698 to 0.299 with soil depth increment, which shows that the content of soil organic matter has a moderate spatial autocorrelation. The soil organic matter in all soil layers met normal distribution after logarithmic transformation. The spatial distribution patterns of soil or- ganic matter and soil moisture were similar; the areas with high organic matter contents were mainly distributed in the south of the study area, with the lowest contents in the middle.

Analysis of thermohaline and current distribution characteristics of Zhejiang and Fujian waters in summer

This paper analyzed the distribution of thermohaline and circulation characteristics of Zhejiang and Fujian waters,based on the cross-sectional thermohaline data and on current data （up to 30 d duration） at fixed-point moorings,collected in the summer of 2006.We also performed low-pass filtering and spectrum analysis on the mooring submersible buoy data.Based on that analysis,we discussed the characteristics of low frequency currents and time-variations in these waters.The main conclusions are as follows.（1） There is a low salinity pinnate area near the Hangzhou Bay in summer,and outside the low salinity area,an obvious salinity front is present from surface to bottom near 123 E.There is also a temperature front below the surface at a corresponding position.（2） Bottom water of the Taiwan Warm Current comes from the subsurface of Kuroshio.（3） The direction of low frequency current at fixed anchor stations is N-NE or S,which mainly depends on the interaction of control currents in this waters.（4） Significant spectral peaks at all mooring stations are typically semidiurnal and diurnal tides.Semidiurnal tidal waves are the main ones in these waters,and have more energy closer to the shore.（5） Significant energy spectral peaks of middle period （3 to 8 d） of currents are responses to weather frequency.（6） Significant energy spectral peaks of long periods at the surface or bottom are probably responses to seasonal wind or bottom friction,while,the long period peaks of other depths can reflect cyclical changes of interactions between currents.We conclude that the pulsation period of the Taiwan Warm Current in these waters is 10-17 d.

Evolution of distribution and content of water in cement paste by low field nuclear magnetic resonance

The low field nuclear magnetic resonance (NMR), as a nondestructive and noninvasive technique, was employed to investigate the water distribution and content in cement paste with different water-to-cement ratio (w/c ratio) during early and later hydration stages. From the water distribution spectrum deduced from relaxation time distribution in paste, it is suggested that the water fills in the capillary pores at initial period, and then diffuses to the mesopores and gel pores in hydration products with the hydration proceeding. The decrease of peak area in water distribution spectrum reflects the transformation from physically bound water to chemically bound water. In addition, based on the connection between relaxation time and pore size, the relative content changes of water in various states and constrained in different types of pores were also measured. The results demonstrate that it is influenced by the formation of pore system and the original water-to-cement ratio in the paste. Consequently, the relative content of capillary water is dropped to less than 2% in the paste with low w/c ratio of 0.3 when being hydrated for 1 d, while the contents are still 16% and 36% in the pastes with w/c ratios of 0.4 and 0.5, respectively.