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.

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.

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.

Effect of droplet characteristics on liquid-phase distribution in spray zone of internal mixing air-mist nozzle

In continuous casting production,droplet characteristics are important parameters for evaluating the nozzle atomization quality,and have a significant impact on the secondary cooling effect and the slab quality.In order to study the behavior of atomized droplets after reaching the slab surface and to optimize the spray cooling effect,the influence of droplet diameter and droplet velocity on the migration behavior of droplets in the secondary cooling zone was analyzed by FLUENT software.Results show that the droplets in the spray zone and on the slab surface are mainly concentrated in the center,thus,the liquid volume fraction in the center is higher than that of either side.As the droplet diameter increases,the region of high liquid volume fraction on the slab surface becomes wider,and the liquid phase distribution in the slab width direction becomes uneven.Although increasing the droplet velocity at the nozzle exit has little effect on droplet diffusion in the spray zone,the distribution becomes more uneven due to more liquid reaches the slab surface per unit time.A prediction formula of the maximum water flow rate on the slab surface for specific droplet characteristics was proposed based on dimensionless analysis and validated by simulated data.A nozzle spacing of 210 mm was recommended under the working conditions in this study,which ensures effective coverage of the spray water over the slab surface and enhances the distribution uniformity of water flow rate in the transverse direction.

Root distribution and influencing factors of dry-sowing and wet-growing cotton plants under different water conditions

To study the effect of soil water and salt environment factors on the root growth of cotton under different moisture control,three different emergence water volumes(60,105,and 150 m^(3)/hm^(2)),two different frequencies(high frequency and low frequency)and one double film cover winter irrigation control treatment(CK:2250 m^(3)/hm^(2))were set up to analyze the spatial distribution patterns of soil water and salt environment and root density in dry sown and wet emerged cotton fields under diffe-rent moisture control conditions.The results show that the soil water content and water infiltration range gradually become larger with the increase of seedling water quantity,and the larger the seedling water quantity,the higher the soil water content.With the same seedling water quantity,the soil water content of the high-frequency(HF)treatment becomes obviously larger.The soil conductivity of each treatment tends to decrease gradually with the increase of seedling water and drip frequency,among which the distribution of soil conductivity of S6 treatment is closest to that of CK.With the increase in soil depth,the soil conductivity tends to increase first and then decrease.Compared with the low-frequency(LF)treatment,the high-frequency treatment shows a significantly deeper soil salt accumulation layer.The root length density(RLD)of cotton gradually increases with the amount of seedling water and the frequency of dripping.The soil layer of root distribution gradually deepens with the amount of seedling water in the vertical direction,and the RLD value in the horizontal direction is significantly greater in the mulched area than that in the bare area between films.This research can serve as a solid scientific foundation for the use of dry sowing and wet emergence techniques in cotton fields in southern Xinjiang.

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.

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.

Distribution and fluxes of suspended sediments in the offshore waters of the Changjiang (Yangtze) Estuary

The offshore waters of the Changjiang Estuary are the transitional areas where river-supplied water and sediment are transported to the sea, and material exchanges occur with the neighbored Hangzhou Bay and the Jiangsu waters. Field observations of currents and sediment properties were conducted to study temporal and spatial distributions of suspended sediments under various dynamical conditions. The high sediment concentrations were found to occur in the western and southern waters of the offshore, and the low concentrations occurred in the eastern and northern waters. This pattern of the suspended sediment concentration （SSC） distribution is obviously influ- enced by the runoff and tidal current. The significant difference of along-estuary SSC distribution indicates that the SSC is reduced gradually from the west to the east, and that in the spring tide is obviously higher than in the neap tide. The methods of mechanism analysis and equal-area grids were used to calculate the suspended sediment fluxes at the typical cross sections. It was found that 44 percent of total suspended sediments from the Changjiang River were deposited in the submarine delta, and more than 27 percent of sediments were transported southernly into the Hangzhou Bay, and only 9 percent of sediments was supplied and exchanged with the northern Jiangsu waters, and about 20 percent of sediments was delivered offshore to the sea.

Online location of seismic damage to a water distribution system

As one of the most important urban lifeline systems,a water distribution system can be damaged under a strong earthquake,and the damage cannot easily be located,especially immediately after the event.This often causes tremendous difficulties to post-earthquake emergency response and recovery activities.This paper proposes a methodology to locate seismic damage to a water distribution system by monitoring water head online at some nodes in the water distribution system.An artificial neural network-based inverse analysis method is developed to estimate the water head variations at all nodes that are not monitored based on the water head variations at the nodes that are monitored.The methodology provides a quick,effective,and practical way to locate seismic damage to a water distribution system.

Particle size distribution and property of bacteria attached to carbon fines in drinking water treatment

The quantitative change and size distribution of particles in the effluents from a sand filter and a granular activated carbon （GAC） filter in a drinking water treatment plant were investigated. The average total concentration of particles in the sand filter effluent during a filter cycle was 148 particles/mL, 27 of which were larger than 2 μm in size. The concentration in the GAC effluent （561 particles/mL） was significantly greater than that in the sand filter effluent. The concentration of particles larger than 2 μm in the GAC filter effluent reached 201 particles/mL, with the amount of particles with sizes between 2 μm and 15 μm increasing. The most probable number （MPN） of carbon fines reached 43 unit/L after six hours and fines between 0.45 μm and 8.0 μm accounted for more than 50%. The total concentration of outflowing bacteria in the GAC filter effluent, 350 CFU （colony-forming units） /mL, was greater than that in the sand filter effluent, 210 CFU/mL. The desorbed bacteria concentration reached an average of 310 CFU/mg fines. The disinfection efficiency of desorbed bacteria was lower than 40% with 1.5 mg/L of chlorine. The disinfection effect showed that the inactivation rate with 2.0 mg/L of chloramine （90%） was higher than that with chlorine （70%）. Experimental results indicated that the high particle concentration in raw water and sedimentation effluent led to high levels of outflowing particles in the sand filter effluent. The activated carbon fines in the effluent accounted for a small proportion of the total particle amount, but the existing bacteria attached to carbon fines may influence the drinking water safety. The disinfection efficiency of desorbed bacteria was lower than that of free bacteria with chlorine, and the disinfection effect on bacteria attached to carbon fines with chloramine was better than that with only chlorine.

Leakage Detection in Water Distribution Network Based on a New Heuristic Genetic Algorithm Model

The leakage control is an important task, because it is associated with some problems such as economic loss, safety concerns, and environmental damages. The pervious methods which have already been devised for leakage detection are not only expensive and time consuming, but also have a low efficient. As a result, the global leakage detection methods such as leak detection based on simulation and calibration of the network have been considered recently. In this research, leak detection based on calibration in two hypothetical and a laboratorial networks is considered. Additionally a novel optimization method called step-by-step elimination method (SSEM) combining with a genetic algorithm (GA) is introduced to calibration and leakage detection in networks. This method step-by-step detects and eliminates the nodes that provide no contribution in leakage among uncertain parameters of calibration of a network. The proposed method initiates with an ordinary calibration for a studied network, follow by elimination of suspicious nodes among adjusted parameters, then, the network is re-calibrated. Finally the process is repeated until the numbers of unknown demands are equal to the desired numbers or the exact leakage locations and values are determined. These investigations illustrate the capability of this method for detecting the locations and sizes of leakages.

Distribution of organochlorine compounds in water, porewater and sediments in Xiamen Harbour

The Concentrations of 18 organochlorine pesticides and 12 polychlorinated biphenyls (PCBs) in water, porewater and sediments from the Xiamen Harbour were analyzed quantitatively. It shows that, the levels of all organochlorine insecticides varied from 6. 60 to 19 .6 ng/dm3 (in water), 11. 9-78. 5 ng/dm3(in porewater) and not detected (ND) - 0. 58 ng/g dry weight (in sediments), and those of total DDTs were in the range ND - 0. 06 ng/g dry weight. Concentrations of PCBs and in- secticides in porewater were higher than in surface water, due to the higher affinity of these hydrophobic compound for sedimentary phase than to water. It implies there would be a potential flux of pollutants from sediments to overlying water. Compared with the concentrations of these pollutants measured in the Xiamen Harbour in 1993, it is one to several magnitude order lower, which suggests their inputs have been decreased in recent years and possible degradation of these compounds. The levels of these pollutants were also compared with other estuaries.

Seepage field distribution and water inflow laws of tunnels in water-rich regions

Currently,the water inrush hazards during tunnel construction,the water leakage during tunnel operation,and the accompanying disturbances to the ecological environment have become the main problems that affect the structural safety of tunnels in water-rich regions.In this paper,a tunnel seepage model testing system was used to conduct experiments of the grouting circle and primary support with different permeability coefficients.The influences of the supporting structures on the water inflow laws and the distribution of the water pressure in the tunnel were analyzed.With the decrease in the permeability coefficient of the grouting circle or the primary support,the inflow rate of water into the tunnel showed a non-linear decreasing trend.In comparison,the water inflow reduction effect of grouting circle was much better than that of primary support.With the increase of the permeability coefficient of the grouting ring,the water pressure behind the primary lining increases gradually,while the water pressure behind the grouting ring decreases.Thus,the grouting of surrounding rock during the construction of water-rich tunnel can effectively weaken the hydraulic connection,reduce the influence range of seepage,and significantly reduce the decline of groundwater.Meanwhile,the seepage tests at different hydrostatic heads and hydrodynamic heads during tunnel operation period were also conducted.As the hydrostatic head decreased,the water pressure at each characteristic point decreased approximately linearly,and the water inflow rate also had a gradual downward trend.Under the action of hydrodynamic head,the water pressure had an obvious lagging effect,which was not conducive to the stability of the supporting structures,and it could be mitigated by actively regulating the drainage rate.Compared with the hydrostatic head,the hydrodynamic head could change the real-time rate of water inflow to the tunnel and broke the dynamic balance between the water pressure and water inflow rate,thereby affecting the stress state on the supporting structures.