Groundwater Pollution Source Identification Using Genetic Algorithm Based Optimization Model

2017 ◽  
Vol 5 (10) ◽  
pp. 65-72
Author(s):  
Md. Ayaz ◽  
Keyword(s):  
Genetic Algorithm ◽  
Groundwater Pollution ◽  
Optimization Model ◽  
Source Identification ◽  
Pollution Source ◽  
Pollution Source Identification

Application of a genetic algorithm to groundwater pollution source identification

2020 ◽  
Vol 589 ◽  
pp. 125343 ◽  
Author(s):  
Kexue Han ◽  
Rui Zuo ◽  
Pengcheng Ni ◽  
Zhenkun Xue ◽  
Donghui Xu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Groundwater Pollution ◽  
Source Identification ◽  
Pollution Source ◽  
Pollution Source Identification

The Influence of Estimated Pollution Range on the Groundwater Pollution Source Identification Method Based on the Simple Genetic Algorithm

2014 ◽  
Vol 587-589 ◽  
pp. 836-841 ◽  
Author(s):  
Yu Qiao Long ◽  
Chun Yong Wu ◽  
Jian Ping Wang
Keyword(s):  
Genetic Algorithm ◽  
Groundwater Pollution ◽  
Optimization Model ◽  
Solution Method ◽  
Pollution Source ◽  
Local Optimum ◽  
Optimization Approach ◽  
Optimum Location ◽  
Migration Direction ◽  
Slight Movement

The optimization approach is common approach to solve complex PSI issues. Most researches on the optimization approach focus on the solution method of the optimization model and improving modeling efficiency. In this paper, we give our effort on the influence of estimated pollution range on the groundwater PSI problem and discuss the efficiency and accuracy of 1D and 2D PSI problems. The estimated pollution range of PSI problem could affect how much calculated time would be consumed. The bigger the estimated range is, the more time is consumed. Increasing the dimension of the PSI problem will increase the estimated range greatly, and leads to a great time consuming. A slight movement of the estimated source in the direction perpendicular to the major migrate direction leads to big bias between the calculated source location and the real location. The chance that optimization model falls into the local optimum location is growing in the major migration direction.

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