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논문검색

Optimal Deployment of Water Resources Based on Multi-Objective Genetic Algorithm

초록

영어

Freshwater is limited resource and it is shrinking rapidly due to the urbanization, contamination and climate change impacts. As a result, raising water demands and insufficient freshwater resources become the main reasons of water conflicts. Optimal water allocation model would be an effective method to achieve the optimal allocation of limited water resources, in terms of the conjunctive use planning and management. In this paper, a multi-objective optimal water resources allocation model is proposed and the social, economic and environmental benefits are regarded as the optimal objective functions. The presented model is applied to a case of planning water resources management in China. Furthermore, simulations and optimization modeling methods have been conducted to solve the allocation model. The Gray Model has been used to predict the fresh water demand and storage of different user parts in 2025 and the Genetic Algorithm technique has been employed to solve the multi-objective problem. The obtained results illustrate how to allocate the quantity of different water resource to different users while achieving maximum social, economic and environmental benefits, which is valuable and helpful to develop a water resources optimal allocation strategy.

목차

Abstract
 1. Introduction
 2. The Proposed Method
 3. Prediction Of Water Demand And Supply
  3.1. Affiliations Prediction Of Water Demand
  3.2. Prediction Of Water Supply
 4. Optimal Water Allocation Model
  4.1. Introduction Of Genetic Algorithm
  4.1. Model Building
 5. Calculation Of Parameters
  5.1. αi And βj
  5.2. Upper And Lower Limits Of Water Demand
  5.3. Weight Coefficients And Other Parameters
 6. Results And Discussions
 7. Conclusions
 9. Conflict Of Interest Statement
 References

저자정보

  • Yong Liu School of Business, South China University of Technology, Guangzhou, China
  • Yongrui Zhuang School of Business, South China University of Technology, Guangzhou, China
  • Nan Lu School of Business, South China University of Technology, Guangzhou, China

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