Cropping structure has a close relationship with the optimal allocation of agricultural water resources. Based on the analysis of the relationship between agricultural water resources and sustainable development, this...Cropping structure has a close relationship with the optimal allocation of agricultural water resources. Based on the analysis of the relationship between agricultural water resources and sustainable development, this paper presents a multi objective fuzzy optimization model for cropping structure and water allocation, which overcomes the shortcoming of current models that only considered the economic objective,and ignored the social and environmental objectives. During the process, a new method named fuzzy deciding weight is developed to decide the objective weight. A case study shows that the model is reliable, the method is simple and objective, and the results are reasonable. This model is useful for agricultural management and sustainable development.展开更多
A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrai...A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrained multi-objective optimization problem. The proposed MOPSO approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system loss objectives and has a diversity-preserving mechanism using an external memory (call “repository”) and a geographically-based approach to find widely different Pareto-optimal solutions. In addition, fuzzy set theory is employed to extract the best compromise solution. Several optimization runs of the proposed MOPSO approach were carried out on the standard IEEE 30-bus test system. The results revealed the capabilities of the proposed MOPSO approach to generate well-distributed Pareto-optimal non-dominated solutions of multi-objective economic load dispatch. Com- parison with Multi-objective Evolutionary Algorithm (MOEA) showed the superiority of the proposed MOPSO approach and confirmed its potential for solving multi-objective economic load dispatch.展开更多
Groundwater is the primary water source in the Kingdom of Saudi Arabia. As result of lack of basic knowledge on irrigation practices, massive abstractions of groundwater occurred in 1980＇s. A Decision Support Linear ...Groundwater is the primary water source in the Kingdom of Saudi Arabia. As result of lack of basic knowledge on irrigation practices, massive abstractions of groundwater occurred in 1980＇s. A Decision Support Linear Goal Programming （LGP） model was developed to determine optimal groundwater irrigation levels, to assess the implications for water management policies, and to estimate welfare impact on producer surplus. Due to the reductions of groundwater in 1980＇s, the Al-Wajid aquifer water levels have dropped in agricultural areas by more than 200 m. Results from this study estimate that the total groundwater of the Al-Wajid aquifer that can be saved is equal to 66 MCM for the first scenario, 147 MCM for the second scenario, and 229 MCM for the third scenario. Regarding the welfare analysis impacts, it is clear that the total gross margin is decreasing up to 7.7% at the end of the year of scenario Ⅲ. Therefore, the third scenario with a water saving increase to 18.1% is recommended as a directive for agricultural policy formation in the future.展开更多
Semiarid loess hilly areas in China are enduring a series of environmental conflicts between urban expansion,cultivated land conservation,soil erosion and water shortage,and require land use allocation to reconcile th...Semiarid loess hilly areas in China are enduring a series of environmental conflicts between urban expansion,cultivated land conservation,soil erosion and water shortage,and require land use allocation to reconcile these environmental conflicts.We argue that the optimized spatial allocation of rural land use can be achieved by a Particle Swarm Optimization (PSO) model in conjunction with multi-objective optimization techniques.Our study focuses on Yuzhong County of Gangsu Province in China,a typical catchment on the Loess Plateau,and proposes a land use spatial optimization model.The model maximizes land use suitability and spatial compactness based on a variety of constraints,e.g.optimal land use structure and restrictive areas,and employs an improved PSO algorithm equipped with a determinant initialization method and a dynamic weighted aggregation (DWA) method to obtain the optimized land use spatial pattern.The results suggest that (1) approximately 4% of land use should be reallocated and these changes would alleviate the environmental conflicts in the study area;(2) the major reshuffling is slope farmland and newly added construction and cultivated land,whereas the unchanged areas are largely forests and basic farmland;and (3) the PSO is capable of optimizing rural land use allocation,and the determinant initialization method and DWA can improve the performance of the PSO.展开更多
文摘Cropping structure has a close relationship with the optimal allocation of agricultural water resources. Based on the analysis of the relationship between agricultural water resources and sustainable development, this paper presents a multi objective fuzzy optimization model for cropping structure and water allocation, which overcomes the shortcoming of current models that only considered the economic objective,and ignored the social and environmental objectives. During the process, a new method named fuzzy deciding weight is developed to decide the objective weight. A case study shows that the model is reliable, the method is simple and objective, and the results are reasonable. This model is useful for agricultural management and sustainable development.
基金Project (Nos. 60074040 and 6022506) supported by the NationalNatural Science Foundation of China
文摘A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrained multi-objective optimization problem. The proposed MOPSO approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system loss objectives and has a diversity-preserving mechanism using an external memory (call “repository”) and a geographically-based approach to find widely different Pareto-optimal solutions. In addition, fuzzy set theory is employed to extract the best compromise solution. Several optimization runs of the proposed MOPSO approach were carried out on the standard IEEE 30-bus test system. The results revealed the capabilities of the proposed MOPSO approach to generate well-distributed Pareto-optimal non-dominated solutions of multi-objective economic load dispatch. Com- parison with Multi-objective Evolutionary Algorithm (MOEA) showed the superiority of the proposed MOPSO approach and confirmed its potential for solving multi-objective economic load dispatch.
文摘Groundwater is the primary water source in the Kingdom of Saudi Arabia. As result of lack of basic knowledge on irrigation practices, massive abstractions of groundwater occurred in 1980＇s. A Decision Support Linear Goal Programming （LGP） model was developed to determine optimal groundwater irrigation levels, to assess the implications for water management policies, and to estimate welfare impact on producer surplus. Due to the reductions of groundwater in 1980＇s, the Al-Wajid aquifer water levels have dropped in agricultural areas by more than 200 m. Results from this study estimate that the total groundwater of the Al-Wajid aquifer that can be saved is equal to 66 MCM for the first scenario, 147 MCM for the second scenario, and 229 MCM for the third scenario. Regarding the welfare analysis impacts, it is clear that the total gross margin is decreasing up to 7.7% at the end of the year of scenario Ⅲ. Therefore, the third scenario with a water saving increase to 18.1% is recommended as a directive for agricultural policy formation in the future.
基金supported in part by the National High-Tech Research & Development Program of China (Grant No.2011AA120304)National Key Technology R&D Program of China(Grant Nos. 2011BAB01B06 and 2006BAB05B06)
文摘Semiarid loess hilly areas in China are enduring a series of environmental conflicts between urban expansion,cultivated land conservation,soil erosion and water shortage,and require land use allocation to reconcile these environmental conflicts.We argue that the optimized spatial allocation of rural land use can be achieved by a Particle Swarm Optimization (PSO) model in conjunction with multi-objective optimization techniques.Our study focuses on Yuzhong County of Gangsu Province in China,a typical catchment on the Loess Plateau,and proposes a land use spatial optimization model.The model maximizes land use suitability and spatial compactness based on a variety of constraints,e.g.optimal land use structure and restrictive areas,and employs an improved PSO algorithm equipped with a determinant initialization method and a dynamic weighted aggregation (DWA) method to obtain the optimized land use spatial pattern.The results suggest that (1) approximately 4% of land use should be reallocated and these changes would alleviate the environmental conflicts in the study area;(2) the major reshuffling is slope farmland and newly added construction and cultivated land,whereas the unchanged areas are largely forests and basic farmland;and (3) the PSO is capable of optimizing rural land use allocation,and the determinant initialization method and DWA can improve the performance of the PSO.
