scholarly journals Analysis of Flood Storage Area Operations in Huai River Using 1D and 2D River Simulation Models Coupled with Global Optimization Algorithms

Geosciences ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 509 ◽  
Author(s):  
Andreja Jonoski ◽  
Ioana Popescu ◽  
Sun Zhe ◽  
Yuhan Mu ◽  
Yiqing He

This article addresses the issue of flood management using four flood storage areas in the middle section of Huai River in China which protect the important downstream city of Bengbu. The same areas are also used by the local population as residential and agricultural zones. An optimization problem is therefore posed, with two objectives of simultaneously minimizing the downstream flood risk in Bengbu city and the storage areas’ economic damages. The methodology involved development of river flood models using HEC-RAS, with varying complexity, such as 1-dimensional (1D) model with storage areas represented as lumped conceptual reservoirs, and 2-dimensional (2D) models with detailed representation of the terrain, land-use and hydrodynamics in the storage areas. Experiments of coupling these models with global optimization algorithms (NSGA-II, PESA-II and SPEA-II) were performed (using the HEC-RAS Controller), in which the two objective functions were minimized, while using stage differences between the river and the storage areas as decision variables for controlling the opening/closing of the gates at the lateral structures that link the river with the storage areas. The comparative analysis of the results indicate that more refined optimal operational strategies that spread the damages across all storage areas can be obtained only with the detailed flood simulation models, regardless of the optimization algorithm used.

10.29007/q4v8 ◽  
2018 ◽  
Author(s):  
Andreja Jonoski ◽  
Ioana Popescu ◽  
Sun Zhe

In this work we present an application of coupled HEC RAS river model with NSGAII multi-objective optimization algorithm, for optimal operations of flood protection storage areas in the downstream part of Huai River in China. During flood, these storage areas are used for decreasing the flood water level downstream in order to protect the important, densely populated city of Bengbu. However, the same storage areas have also been used by local population, as both residential and agricultural zones, with high damage potential in case of flooding. The application investigates optimal operations of opening and closing the gates that connect the storage areas to the main river, which minimize the damage in the storage areas without compromising the protection of Bengbu. Two objectives are formulated related to: 1) downstream risk of flooding in Bengbu, and 2) damages in the storage areas. Decision variables are stage differences between the river and a given storage area, used for controlling gates operations (opening and closing). The coupling is performed in MATLAB using recently available HEC RAS API, known as HEC-RAS Controller. Initial results, obtained using flood hydrograph from the summer of 2007, indicate possible optimal operations, with selective usage of the storage areas.


2021 ◽  
Vol 1 ◽  
pp. 113-117
Author(s):  
Dmitry Syedin ◽  

The work is devoted to the hybridization of stochastic global optimization algorithms depending on their architecture. The main methods of hybridization of stochastic optimization algorithms are listed. An example of hybridization of the algorithm is given, the modification of which became possible due to taking into account the characteristic architecture of the M-PCA algorithm.


Author(s):  
Nicholas R. Radcliffe ◽  
David R. Easterling ◽  
Layne T. Watson ◽  
Michael L. Madigan ◽  
Kathleen A. Bieryla

Author(s):  
Arion de Campos Jr. ◽  
Aurora T. R. Pozo ◽  
Silvia R. Vergilio

The Web service composition refers to the aggregation of Web services to meet customers' needs in the construction of complex applications. The selection among a large number of Web services that provide the desired functionalities for the composition is generally driven by QoS (Quality of Service) attributes, and formulated as a constrained multi-objective optimization problem. However, many equally important QoS attributes exist and in this situation the performance of the multi-objective algorithms can be degraded. To deal properly with this problem we investigate in this chapter a solution based in many-objective optimization algorithms. We conduct an empirical analysis to measure the performance of the proposed solution with the following preference relations: Controlling the Dominance Area of Solutions, Maximum Ranking and Average Ranking. These preference relations are implemented with NSGA-II using five objectives. A set of performance measures is used to investigate how these techniques affect convergence and diversity of the search in the WSC context.


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