The interval copula-measure Me based multi-objective multi-stage stochastic chance-constrained programming for seasonal water resources allocation under uncertainty

2020 ◽  
Author(s):  
Youzhi Wang ◽  
Ping Guo
Keyword(s):  
Water Resources ◽  
Resources Allocation ◽  
Chance Constrained Programming ◽  
Water Resources Allocation ◽  
Multi Objective ◽  
Multi Stage ◽  
Constrained Programming

scholarly journals Applying an Extended Fuzzy Parametric Approach to the Problem of Water Allocations

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
T. Y. Xu ◽  
X. S. Qin
Keyword(s):  
Water Resources ◽  
Objective Function ◽  
Parametric Programming ◽  
Resources Allocation ◽  
Chance Constrained Programming ◽  
Water Resources Allocation ◽  
Parameter Uncertainties ◽  
Constrained Programming ◽  
System Benefit ◽  
Decision Alternatives

An extended fuzzy parametric programming (EFPP) model was proposed for supporting water resources allocation problems under uncertainty. EFPP deals with flexible constraints (i.e., fuzzy relationships) by allowing violation of constraints at certain satisfaction degrees (i.e.,αlevels) and employs fuzzy ranking method to handle trapezoidal-shaped fuzzy coefficients. The objective function is defuzzified by usingβcuts and weighting factors. The applicability of EFPP was demonstrated by a numerical example and a water resources allocation case. A series of decision alternatives at various satisfaction degrees were obtained. Generally, the higher theαlevel, the lower the system benefit. In comparison, theβlevel in the objective function posed less sensitive impacts on both objective function and model solutions. The reliability of EFPP was tested by comparing its solutions with those from fuzzy chance constrained programming (FCCP). The results indicated that EFPP performed equally well with FCCP in addressing parameter uncertainties, but it demonstrated a wider applicability due to its extended capacity of handling fuzzy relationships in the model constraints.

A study of multi-objective dynamic water resources allocation modeling of Huai River

2015 ◽  
Vol 15 (4) ◽  
pp. 817-824 ◽  
Author(s):  
Jing Peng ◽  
Ximin Yuan ◽  
Lan Qi ◽  
Qiliang Li
Keyword(s):  
Water Resources ◽  
Dynamic Balance ◽  
Supply And Demand ◽  
Low Flow ◽  
Resources Allocation ◽  
Time Interval ◽  
Water Resources Allocation ◽  
Allocation Model ◽  
Multi Objective ◽  
Huai River

Water resources supply and demand has become a serious problem. Water resources allocation is usually a multi-objective problem, and has been of concern for many researchers. In the north of China, the lack of water resources in the Huai River Basin has handicapped the development of the economy, especially badly in the low-flow period. So it is necessary to study water resources allocation in this area. In this paper, a multi-objective dynamic water resources allocation model has been developed. The developed model took the overall satisfaction of water users in a time interval as the objective function, applied an improved simplex method to solve the calculation, considered the overall users' satisfaction variation with time, and followed the principle that the variation of the system satisfaction within adjacent periods of time must be minimal. The established model was then applied to the Huai River, for the present situation (2010), short-term (2020) and long-term (2030) planning timeframes. From the calculation results, the overall satisfaction in late May and mid September in 2030 was 0.65 and 0.70. After using the model allocation optimization, the overall satisfaction was improved, increasing to 0.78 and 0.79, respectively, thus achieving the dynamic balance optimization of water resources allocation in time and space. This model can provide useful decision support in water resources allocation, when it is used to alleviate water shortages occurring in the low-flow period.

A Fair Approach for Multi-Objective Water Resources Allocation

2019 ◽  
Vol 33 (10) ◽  
pp. 3633-3653 ◽  
Author(s):  
Jing Tian ◽  
Shenglian Guo ◽  
Dedi Liu ◽  
Zhengke Pan ◽  
Xingjun Hong
Keyword(s):  
Water Resources ◽  
Resources Allocation ◽  
Water Resources Allocation ◽  
Multi Objective

scholarly journals Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China

2020 ◽  
Vol 12 (4) ◽  
pp. 1337 ◽  
Author(s):  
Junfei Chen ◽  
Cong Yu ◽  
Miao Cai ◽  
Huimin Wang ◽  
Pei Zhou
Keyword(s):  
Water Resources ◽  
Water Demand ◽  
Optimal Allocation ◽  
Pso Algorithm ◽  
Resources Allocation ◽  
Urban Water ◽  
Water Resources Allocation ◽  
Multi Objective ◽  
Guarantee Rate ◽  
Allocation Plans

With the rapid increase of water demand in urban life, ecology and production sectors, the problem of water resources allocation has become increasingly prominent. It has hindered the sustainable development of urban areas. Based on the supply of various water sources and the water demand of different water users, a multi-objective optimal allocation model for urban water resources was proposed. The model was solved using the algorithm of particle swarm optimization (PSO). The algorithm has a fast convergence and is both simple and efficient. In this paper, the conflict over Kunming’s water resources allocation was taken as an example. The PSO algorithm was used to obtain optimized water resources allocation plans in the year 2020 and 2030, under the circumstances of a dry year (inflow guarantee rate p = 0.825) and an unusually dry year (inflow guarantee rate p = 0.885), respectively. The results showed that those allocation plans can lower the future potential water shortage rates of Kunming. At the same time, the interests of different sectors can all be satisfied. Therefore, conflicts over urban water use can be effectively alleviated.

scholarly journals Comparison of Transboundary Water Resources Allocation Models Based on Game Theory and Multi-Objective Optimization

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1421
Author(s):  
Jisi Fu ◽  
Ping-An Zhong ◽  
Bin Xu ◽  
Feilin Zhu ◽  
Juan Chen ◽  
...  
Keyword(s):  
Water Resources ◽  
Pareto Front ◽  
Resources Allocation ◽  
Game Model ◽  
Water Resources Allocation ◽  
Multi Objective Optimization ◽  
Transboundary Water ◽  
Nsga Ii ◽  
Multi Objective ◽  
Transboundary Water Resources

Transboundary water resources allocation is an effective measure to resolve water-related conflicts. Aiming at the problem of water conflicts, we constructed water resources allocation models based on game theory and multi-objective optimization, and revealed the differences between the two models. We compare the Pareto front solved by the AR-MOEA method and the NSGA-II method, and analyzed the difference between the Nash–Harsanyi Leader–Follower game model and the multi-objective optimization model. The Huaihe River basin was selected as a case study. The results show that: (1) The AR-MOEA method is better than the NSGA-II method in terms of the diversity metric (Δ); (2) the solution of the asymmetric Nash–Harsanyi Leader–Follower game model is a non-dominated solution, and the asymmetric game model can obtain the same water resources allocation scheme of the multi-objective optimal allocation model under a specific preference structure; (3) after the multi-objective optimization model obtains the Pareto front, it still needs to construct the preference information of the Pareto front for a second time to make the optimal solution of a multi-objective decision, while the game model can directly obtain the water resources allocation scheme at one time by participating in the negotiation. The results expand the solution method of water resources allocation models and provide support for rational water resources allocation.

A Multi-Objective Optimal Water Resources Allocation Process

1981 ◽  
Vol 14 (2) ◽  
pp. 3901-3906
Author(s):  
Y. Hagihara ◽  
K. Hagihara ◽  
Y. Nakagawa ◽  
H. Watanabe
Keyword(s):  
Water Resources ◽  
Resources Allocation ◽  
Water Resources Allocation ◽  
Multi Objective ◽  
Allocation Process
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