Region Water Resources Optimal Allocation Based on Multi-Objective Genetic Algorithm

2013 ◽  
Author(s):  
Feng Kepeng ◽  
Tian Juncang
Keyword(s):  
Genetic Algorithm ◽  
Water Resources ◽  
Optimal Allocation ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Water Resources Optimal Allocation

scholarly journals Evaluation of a Multi-Objective Genetic Algorithm for Low Impact Development in an Overcrowded City

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2010 ◽  
Author(s):  
Hao-Che Ho ◽  
Shih-Wei Lin ◽  
Hong-Yuan Lee ◽  
Cheng-Chia Huang
Keyword(s):  
Genetic Algorithm ◽  
Urban Areas ◽  
Optimal Allocation ◽  
Low Impact Development ◽  
Return Periods ◽  
Detention Ponds ◽  
Study Region ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Study Results

Sustainability and resilience are up-to-date considerations for urban developments in terms of flood mitigation. These considerations usually pose a new challenge to the urban planner because the achievement of a sustainable design through low impact development (LID) practices would be affected by the selection and the distribution of them. This study proposed a means to optimize the distribution of LIDs with the concept of considering the reduction of the flood peak and the hydrologic footprint residence (HFR). The study region is a densely populated place located in New Taipei City. This place has been developing for more than 40 years with completive sewer systems; therefore, the design must consider the space limitations. The flood reduction induced by each LID component under different rainfall return periods was estimated, and then the detention ponds were also conducted to compare the improvements. The results showed that the performance of LIDs dramatically decreased when the return periods were larger than ten years. A multi-objective genetic algorithm (MOGA) was then applied to optimize the spatial distribution of LIDs under different budget scenarios, and to decide the priority of locations for the LID configuration. Finally, the Monte Carlo test was used to test the relationship between the optimal space configuration of LIDs and the impermeability of the study region. A positive correlation was uncovered between the optimal allocation ratio and the impermeable rate of the partition. The study results can provide general guidelines for urban planners to design LIDs in urban areas.

The Study of Water Resources Optimal Allocation of South-North Project Receiving Area

2013 ◽  
Vol 385-386 ◽  
pp. 420-423
Author(s):  
Bin Liu ◽  
Jin Xia Sha ◽  
Zhi Hong Yan ◽  
Ting Ting Zhang
Keyword(s):  
Water Resources ◽  
Optimal Allocation ◽  
Rapid Development ◽  
Theory Building ◽  
Planning Theory ◽  
Water Resources Planning ◽  
Multi Objective ◽  
Handan City ◽  
Resources Planning ◽  
Water Resources Optimal Allocation

With the rapid development of economy, the shortage of water resources became more serious at the eastern of Handan city, it is important to allocate the limited water resources reasonably. Based on the multi-objective planning theory, building up the model of the optimal allocation water resources. The goal of the model targeted at the maximum benefits of the economy, the society and the environment, which solved by PSO, to acquire the water resources optimal allocation program of different guaranteed rate in 2030, and supply the basis for the water resources planning and management. The results of optimal allocation show that the PSO is feasible in the water resources optimal allocation.

Water Resources Optimal Allocation Based on Multi-Objective Differential Evolution Algorithm

2013 ◽  
Vol 278-280 ◽  
pp. 1271-1274 ◽  
Author(s):  
Ke Peng Feng ◽  
Jun Cang Tian
Keyword(s):  
Water Resources ◽  
Differential Evolution ◽  
Optimal Allocation ◽  
Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Population Based ◽  
Allocation Model ◽  
Multi Objective ◽  
Regional Water ◽  
Water Resources Optimal Allocation

Differential evolution is a simple and powerful globally optimization new algorithm. It is a population-based, direct search algorithm, and has been successfully applied in various fields. Optimal allocation of water resources is an important part of the planning of water resources. Traditional planning methods prove insufficient for the multi-objective system of water resources. In this paper, multi-objective differential evolution(MODE) algorithm applied to the regional water resources optimal allocation, through definition of economic, social, Eco-environmental three objective function and the constraints, the regional water resources optimal allocation model has been established, and then multi-objective genetic algorithm is used to solve the model .The model gets different results for optimal allocation water resources of Ningxia in 2030(Guarantee rate of water supply 50% and 75%). The result of example proves that the method is reasonable and feasible in the application of region water resources optimal allocation.

scholarly journals Multi-objective Water Resources Optimum Allocation Scheme Based on Improved Standard Cuckoo Searching Algorithm (ISCSA)

2021 ◽  
Author(s):  
Ke Zhou
Keyword(s):  
Water Resources ◽  
Water Supply ◽  
Optimal Allocation ◽  
Optimal Solution ◽  
Local Optimum ◽  
Ecological Benefits ◽  
Multi Objective ◽  
Intelligent Optimization Algorithm ◽  
Water Resources Optimal Allocation

Abstract The standard cuckoo searching algorithm(SCSA)is a population intelligent optimization algorithm, which is also a new heuristic searching algorithm. The advantages of SCSA (such as convenient operation, heuristic searching, etc.) make it easy to find the optimal solution and maintain wider searching range. However, SCSA also has some drawbacks, such as long searching time, easy to fall into local optimum. In order to solve the problems existed in SCSA, in this paper, the improved standard cuckoo searching algorithm (ISCSA) was studied, which includes chaotic initialization and Gaussian disturbed algorithm. As a case study, taking economic, social and ecological benefits as the objective function, the multi-objective water resources optimal allocation models were constructed in Xianxiang Region, China. The ISCSA was applied to solve the water allocation models and the multi-objective optimal water supply scheme for Xinxiang region was obtained. The water resources optimal allocation schemes in the planning level year (2025) for 12 water supply sub-regions were predicted. The desirable eco-environment and benefits were achieved using the studied methods. The results show that the ISCSA has obvious advantages in the solution of water resources optimal allocation and planning.

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