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Fuzzy Based Optimal Allocation of Resources for Grid Scheduling
G. Murugesan,C. Chellappan
Research Journal of Applied Sciences , 2012, DOI: 10.3923/rjasci.2012.119.125
Abstract: Grid computing is becoming a popular way of providing high performance computing for many process intensive, scientific and business applications. Grid computing consists of large sets of diverse, geographically distributed resources that are collected into a virtual computer for high performance computation. Resource allocation in grid computing is the challenging task due the heterogeneity and dynamic nature of resources. Many of the researches have been done to develop a better resource allocation model. But in most of the work they follow either the time as decision parameter or the cost as decision parameter. A very few work had been focused for both the parameter also they are trying to improve the grid resource performance. In this study, researchers developed a mathematical model as an economic model with the aim to benefit the grid user. The Resource Allocation Model in grid computing consists of two components; resource selection and resource sequencing. Researchers used the fuzzy logic technique to perform the resource selection and resource sequencing. The performance of the mathematical model is evaluated with an extensive set of input values to demonstrate the practical use of the model. The result shows that the approach outperform other models by minimizing the time and cost of the application of the grid user.
Discussion on Optimal Allocation of Administrative Resources Used to Crack Down on Illegal Industry Chain
Songbiao HE,Fang WANG,Wenfeng LI
Management Science and Engineering , 2012, DOI: 10.3968/j.mse.1913035x20120601.z2499
Abstract: Illegal activities usually present industry chain characteristics, such as pornographic chain, piratical chain, oil-related illegal industry chain, and so on. Governments need to make heavy blows on illegal industry chains to maintain the healthy development of society and economy. As we all know, governmental blow activities need certain administrative resources. However different resource allocation modes cause different blow effects. This paper designed an optimal allocation model of administrative resources to purchase the maximum success rate of blow action subjected to certain administrative resources based on probability theory according to the characteristics of illegal industry chain. Key words: Industry Chain; Administrative Resource; Optimal Allocation
Optimal Management of Irrigation Water Allocation and Cropping Pattern Utilizing Conjunctive Use of Surface and Subsurface Water Resources  [cached]
M. K. Shaabani,T. Honar,M. Zibaei
Journal of Science and Technology of Agriculture and Natural Resources , 2008,
Abstract: Limitations of rainfall and surface water resources farmers have to use both surface and subsurface resources for growing different crops. In this study optimal management of irrigation water allocation and cropping pattern utilizing conjunctive use of surface and subsurface water resources is studied. Also the effect of reducing water consumption in different growth stages with different irrigation strategies for major crops (wheat, barely, corn, sugar beet, rice) in Fars province was studied. The results of the study showed that optimal cropping pattern for the first season would be mainly wheat and in the second season would be corn and rice. Also in this model different policies for decreasing water demand were studied. Since crop water requirement in the second season is higher than the first season, therefore restriction on including high water consuming crops in the second season would be the best choice in the cropping pattern.
Combination of Pareto ant colony algorithm with remote sensing for optimal allocation of water resources

HOU Jing-wei,KONG Yun-feng,SUN Jiu-lin,

控制理论与应用 , 2012,
Abstract: To solve the optimal allocation problem of water resources with Pareto ant colony algorithm (PACA) and remote sensing (RS), we develop an optimization model in pixel scales. This model produces the largest social, economic, and environmental benefits under constraints on water supply, water demand and water quality. By limiting the local pheromone scope, dynamically updating the global pheromone and filtering the Pareto solution set, we improve the PACA to make ants move towards the optimal border with higher pheromone density, and enhance the global search capability and raise the convergence rate. To validate the feasibility and effectiveness of the PACA, a county in central China is selected as the simulation object, from which the data of the land-use pattern is obtained by using the RS technology. By solving the multi-objective model, we obtain the optimal allocation scheme for water resources with the aid of PACA on a raster map. Performance and convergence of the PACA are compared with those of the genetic algorithm (GA) and BP neural network algorithm (BP-ANN); results show that PACA can effectively solve the large-scale, multi-objective optimization model of water resources with stronger global search capability and higher convergence rate and precision.
Study on the Sustainable Development Oriented Optimal Allocation to Region Water Resources

FENG Yao-long,HAN Wen-xiu,WANG Hong-jiang{,},LIAN Ji-jian,

系统工程理论与实践 , 2003,
Abstract: The connotations and principles of the sustainable development oriented optimal allocation to region water resources are analyzed systematically. The model of the optimal allocation is established. The practicable methods and procedures for the model are presented, and the case study is done by taking the water resources allocation in the level year 2010 of Tianjin city as the object.
Optimal Allocation of Water Resources Based on the Multi-Objective Fish-Ant Colony Algorithm

HOU Jingwei,KONG Yunfeng,SUN Jiulin,

资源科学 , 2011,
Abstract: To resolve complex problems on optimal allocation of water resources with intelligent optimal methods, a multi-objective optimization model was built and the multi-objective fish-ant colony algorithm (MFACA) was designed. This model, based on principles of efficiency, fairness, and harmoniousness, is aimed at producing the largest economic, social, and environmental benefits. The objective of economic benefit is the largest direct economic benefit produced by regional water supply. The objective of social benefit is referred to as the smallest regional water deficit. The objective of environmental benefit is to ensure the smallest discharge of major contaminants. Constraints included water supply, water demand, water settings, economic development, and its harmony. In this model, constraints of water supply include possible water yield and ground water yield. Constraints of water demand include living, industrial, agricultural, and environmental water. Constraints of water settings include overall merit index and water quality. The optimal allocation model had the characteristics of large-scale system, multiple objectives, multiple constraints, multiple levels, and multiple associations. To solve this complicated model, the multi-objective fish-ant colony algorithm was established in accordance with the integration of pheromone positive feedback of the ant colony optimization (ACO) and fast track change and jumping out of local extremum of the artificial fish-swarm algorithm (AFA). A swarm degree in the AFA was used to avoid possible premature problems at the initial stage of ACO. It was not strict for MFACA to set parameters and initial values of a mathematical model. The objective functions and constraints were not necessarily continuous and differentiable. This algorithm has a faster convergence rate and a higher optimization power. In order to validate the feasibility and effectiveness of the MFACA, surveys were done in Zhenping County, Henan Province, China. Data of water resources and other relevant socioeconomic information were obtained and input into a database. Water yield with different planning years and different guaranteed rates was optimized. The largest economic, social, and environmental benefits were effectively calculated with the model and the MFACA. To compare different effects and convergences amongst MFACA, AFA, and ACO, emulations were demonstrated after the same initial parameters of the model were input into MFACA, AFA and ACO, respectively. Optimal solutions were obtained at about the 89th iteration for MFACA, about the 130th iteration for AFA, and about the 110th iteration for ACO in the best condition. The MFACA showed the best result and the fastest convergence rate amongst the three algorithms. It has been shown to be a promising tool for optimal allocation of water resources.
Research on Survey and Development of High-Quality Education Resources Allocation from the Perspective of Fairness

张志泉, 姜正国
Advances in Education (AE) , 2015, DOI: 10.12677/AE.2015.54013
Transformation from a big country to a powerful country with huge human resources is the stra-tegic target of education development in the next ten years in China. Reasonable allocation and development of high-quality education resources are conducive to the realization of this goal. Re-viewing the evolution process of education resources allocation and the problems existing from the perspective of fairness since the founding of the People’s Republic of China can help us make dialectical thinking and find ways to solve the problems in educational resources allocation and utilization.
Optimal Water Resources Allocation in Shiyanghe River Basin Sased onMulti-Objective Analysis

MA Guo-jun,LIN Dong,LIU Jun-di,ZHANG Mei-hua,CHEN Nian-lai,
,林 栋,刘君娣,

中国沙漠 , 2008,
Abstract: Water resources rational allocation is one of the efficient ways to solving water shortage. A model for optimal water resource allocation of Shiyanghe river basin was established in the paper by applying the method of multi-objectives and multi-stages decision and in premise of analyzing the relationship between the sustainable development and the bearing capacity of regional water resources in this region. Based on the model the optimal allocation of water resources for 2010 and 2020 were calculated and presented. The results showed that problems such as uncertainty and fuzzy theory often encountered in water resources allocation could be solved through uncertainty or fuzzy pattern recognition model. To an alternating simulation and optimal coupled model that is and object-oriented can solve many practical problems in water resources allocation.
Discussion on Optimal Allocation Methods of Water and Land Resources at the Watershed Scale

GENG Yan-hui,MIN Qing-wen,CHENG Sheng-kui,

资源科学 , 2007,
Abstract: Although there are lots of researches on optimal allocation of water or land resource at present, few have combined the two factors with each other both in macro- and micro-scale. The study in macro-scale would help to promote regional allocation efficiency and, in contrast, the study in microscopic scale would help to raise resources utilization efficiency. In general, the researches on macro-scale focus on adjusting crops structure, making master plan of irrigation for irrigated agriculture in arid and semi-arid areas. But the researches in micro-scale allocation all more emphasize to achieve high economic benefits. Now people pay more and more attention to the study on establishing models and adjusting parameters in order to improve degraded ecosystems and ecosystem services to meet the increasing needs to regional sustainable development. However, many researchers pay more attentions to single elements than the couple system with water and land resources, especially their interaction. The mathematical methods to realize optimal allocation have transformed from qualitative to quantitative, and lots of models have been used in the process, such as general linear programming, grey linear programming, dynamic programming, multi-objection decision-making and system dynamics model. These methods have different merits and application scales. It is no doubt that the dissection and comparison for the models are very important, but we should not ignore to improve their operational efficiency and to find the port to connect different methods. And, it is necessary to transform and combine the results referring to both of macro- and micro-scales. Currently, scholars pay lots of attentions on Decision Support System, which combine Remote Sensing, Geographic Information System and Global Position System (3"S") techniques with special models, so as to provide enough supports to water and land resources optimal allocation and management. Through analyzing these methods for optimal allocation, the in-depth studies were suggested as following: 1) to further perfect the theories and techniques of optimization allocation viewing from the systematical point combining with the nature of watershed; 2) to strengthen the integration between GIS and quantitative models; 3) to reinforce the study on some related problems liking the quantification of regional ecological benefits, the determination of ratio of ecological and economic benefits, the theories and methods of ecological water requirement, the hydrological effects of forest vegetation, the key techniques of agricultural water-saving and water resource management; and 4) to develop the decision support systems for water and land resources optimal allocation in watershed scale.
Optimal allocation of water resources based on ant colony particle swarm algorithm

- , 2015,
Abstract: 【目的】对区域水资源的合理优化配置进行研究,为区域经济的发展、水资源的合理开发利用和节水型社会的建立提供参考。【方法】建立以经济、社会、生态环境效益为目标函数,各目标加权和为最优解的水资源优化配置模型,采用蚁群 粒子群混合算法对模型进行求解,并对渭北工业区进行水资源优化配置的实例分析,通过原供水量与优化配置水量的比较验证所建立模型的合理性。【结果】经计算,75%保证率下渭北工业区水资源的配置结果为:2015年地表水、地下水、外调水、中水供水量分别为1 747.30,13 244.84,12 905.95和1 060.23万m3;2020年各水源供水量分别为2 019.19,12 214.42,23 530.42和1 798.60万m3;与原始供水量相比,2015年和2020年总供水量分别减少312.73和421.11万m3,表现在农业供水量减少,生活、工业、生态用水均达到供需平衡。【结论】基于蚁群-粒子群混合算法的水资源优化配置结果合理,可作为研究区水资源合理开发利用决策的参考;蚁群 粒子群混合算法收敛速度快,寻优性能优越,可用于水资源优化配置的分析。
【Objective】This study focused on optimal allocation of regional water resources to provide reference for regional economic development,rational development and utilization of water resources and building water-saving society.【Method】To establish an optimal allocation model of water resources including economic,social,ecological and environmental benefits with the optimal solution of the weighted sum of each objective,the hybrid ant colony and particle swarm optimization algorithms were adopted to solve the model.Weibei Industrial Zone was taken as an example to analyze the optimal allocation of water resources.Then the comparison of the original water supply and the optimal allocation of water was conducted to verify the rationality of the established model.【Result】Through calculation,the water resources allocation results with 75% guarantee rate were obtained:The water supplies of surface water,ground water,water transfer and wastewater reuse in 2015 were 1 747.30×104 m3,13 244.84×104 m3,12 905.95×104 m3 and 1 060.23×104 m3,respectively and those in 2020 were 2 019.19×104 m3,12 214.42×104 m3,23 530.42×104 m3 and 1 798.60×104 m3,respectively.Compared with the original water supply,the total water supplies in 2015 and 2020 were reduced by 312.73×104 m3 and 421.11×104 m3,respectively.The results were based on reduction in agricultural water supply and balance of supply and demand in residential,industrial and ecological water uses.【Conclusion】Ant colony-particle swarm algorithm based optimal allocation was reasonable,and can be used as reference for the rational development and utilization of water resources in the study area.The ant and particle swarm hybrid algorithm had fast convergence speed and optimal performance,which can be used for the analysis of optimal allocation of water resources
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