Multi-Water Resources Optimal Allocation Based on Multi-Objective Uncertain Chance-Constrained Programming Model

2020 ◽  
Vol 34 (15) ◽  
pp. 4881-4899
Author(s):  
Xiaona Li ◽  
Xiaosheng Wang ◽  
Haiying Guo ◽  
Weimin Ma
Keyword(s):  
Water Resources ◽  
Optimal Allocation ◽  
Programming Model ◽  
Chance Constrained Programming ◽  
Multi Objective ◽  
Constrained Programming ◽  
Water Resources Optimal Allocation

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.

scholarly journals Inexact Multistage Stochastic Chance Constrained Programming Model for Water Resources Management under Uncertainties

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Hong Zhang ◽  
Minghu Ha ◽  
Hongyu Zhao ◽  
Jianwei Song
Keyword(s):  
Water Resources ◽  
Stochastic Programming ◽  
Water Resources Management ◽  
Water Allocation ◽  
Programming Model ◽  
Management Systems ◽  
Chance Constrained Programming ◽  
Multistage Stochastic Programming ◽  
Resources Management ◽  
Constrained Programming

In order to formulate water allocation schemes under uncertainties in the water resources management systems, an inexact multistage stochastic chance constrained programming (IMSCCP) model is proposed. The model integrates stochastic chance constrained programming, multistage stochastic programming, and inexact stochastic programming within a general optimization framework to handle the uncertainties occurring in both constraints and objective. These uncertainties are expressed as probability distributions, interval with multiply distributed stochastic boundaries, dynamic features of the long-term water allocation plans, and so on. Compared with the existing inexact multistage stochastic programming, the IMSCCP can be used to assess more system risks and handle more complicated uncertainties in water resources management systems. The IMSCCP model is applied to a hypothetical case study of water resources management. In order to construct an approximate solution for the model, a hybrid algorithm, which incorporates stochastic simulation, back propagation neural network, and genetic algorithm, is proposed. The results show that the optimal value represents the maximal net system benefit achieved with a given confidence level under chance constraints, and the solutions provide optimal water allocation schemes to multiple users over a multiperiod planning horizon.

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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