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.

scholarly journals Weighted Bankruptcy Rules and Transboundary Water Resources Allocation

2015 ◽  
Vol 29 (7) ◽  
pp. 2303-2321 ◽  
Author(s):  
Hojjat Mianabadi ◽  
Erik Mostert ◽  
Saket Pande ◽  
Nick van de Giesen
Keyword(s):  
Water Resources ◽  
Resources Allocation ◽  
Water Resources Allocation ◽  
Transboundary Water ◽  
Transboundary Water Resources

Optimization of Vehicle-Borne Radar Antenna Pedestal Based on Modified NSGA-II

2014 ◽  
Vol 945-949 ◽  
pp. 2241-2247
Author(s):  
De Gao Zhao ◽  
Qiang Li
Keyword(s):  
Pareto Front ◽  
Optimization Problems ◽  
Population Diversity ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Sorting Process ◽  
Definition Of ◽  
Radar Antenna ◽  
Modified Algorithm

This paper deals with application of Non-dominated Sorting Genetic Algorithm with elitism (NSGA-II) to solve multi-objective optimization problems of designing a vehicle-borne radar antenna pedestal. Five technical improvements are proposed due to the disadvantages of NSGA-II. They are as follow: (1) presenting a new method to calculate the fitness of individuals in population; (2) renewing the definition of crowding distance; (3) introducing a threshold for choosing elitist; (4) reducing some redundant sorting process; (5) developing a self-adaptive arithmetic cross and mutation probability. The modified algorithm can lead to better population diversity than the original NSGA-II. Simulation results prove rationality and validity of the modified NSGA-II. A uniformly distributed Pareto front can be obtained by using the modified NSGA-II. Finally, a multi-objective problem of designing a vehicle-borne radar antenna pedestal is settled with the modified algorithm.

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.

Multi-objective optimization of a hybrid electromagnetic suspension system for ride comfort, road holding and regenerated power

2016 ◽  
Vol 23 (5) ◽  
pp. 782-793 ◽  
Author(s):  
Mansour Ataei ◽  
Ehsan Asadi ◽  
Avesta Goodarzi ◽  
Amir Khajepour ◽  
Mir Behrad Khamesee
Keyword(s):  
Pareto Front ◽  
Ride Comfort ◽  
Optimization Method ◽  
Suspension System ◽  
Multi Objective Optimization ◽  
Damping Force ◽  
Nsga Ii ◽  
Electromagnetic Suspension ◽  
Multi Objective ◽  
Electromagnetic Component

This paper reports work on the optimization and performance evaluation of a hybrid electromagnetic suspension system equipped with a hybrid electromagnetic damper. The hybrid damper is configured to operate with hydraulic and electromagnetic components. The hydraulic component produces a large fail-safe baseline damping force, while the electromagnetic component adds energy regeneration and adaptability to the suspension. For analyzing the system, the electromagnetic component was modeled and integrated into a 2DOF quarter-car model. Three criteria were considered for evaluating the performance of the suspension system: ride comfort, road holding and regenerated power. Using the genetic algorithm multi-objective optimization (NSGA-II), the suspension design was optimized to improve the performance of the vehicle with respect to the selected criteria. The multi-objective optimization method provided a set of solutions called Pareto front in which all solutions are equally good and the selection of each one depends on conditions and needs. Among the given solutions in the Pareto front, a small number of cases, with different design purposes, were selected. The performances of the selected designs were compared with two reference systems: a conventional and a nonoptimized hybrid suspension system. The results show that the ride comfort and road holding qualities of the optimized hybrid system are improved, and the regenerated power is considerably increased.

Multi-Objective Optimization of the Impingement-Film Cooling Structure of a Gas Turbine Endwall Using Conjugate Heat Transfer Simulations

2017 ◽  
Vol 10 (2) ◽  
Author(s):  
Zhongran Chi ◽  
Haiqing Liu ◽  
Shusheng Zang
Keyword(s):  
Heat Transfer ◽  
Film Cooling ◽  
Conjugate Heat Transfer ◽  
Pareto Front ◽  
Parametric Design ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Lift Off ◽  
Optimization Search

This paper discusses the approach of cooling design optimization of a high-pressure turbine (HPT) endwall with applied 3D conjugate heat transfer (CHT) computational fluid dynamics (CFD). This study involved the optimization of the spacing of impingement jet array and the exit width of shaped holes, which are different for each cooling cavity. The optimization objectives were to reduce the wall-temperature level and to increase the aerodynamic performance. The optimization methodology consisted of an in-house parametric design and CFD mesh generation tool, a CHT CFD solver, a database of CFD results, a metamodel, and an algorithm for multi-objective optimization. The CFD tool was validated against experimental data of an endwall at CHT conditions. The metamodel, which could efficiently estimate the optimization objectives of new individuals without CFD runs, was developed and coupled with nondominated sorting genetic algorithm II (NSGA II) to accelerate the optimization process. Through the optimization search, the Pareto front of the problem was found in each iteration. The accuracy of metamodel with more iterations was improved by enriching database. But optimal designs found by the last iteration are almost identical with those of the first iteration. Through analyzing extra CFD results, it was demonstrated that the design variables in the Pareto front successfully reached the optimal values. The optimal pitches of impingement arrays could be decided accommodating the local thermal load while avoiding jet lift-off of film coolant. It was also suggested that cylindrical film holes near throat should be beneficial to both aerodynamic and cooling performances.

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