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Study of optimal allocation of water resources in Dujiangyan irrigation district of China based on an improved genetic algorithm
Author(s) -
Ruihuan Li,
Yingli Chang,
Zhaocai Wang
Publication year - 2020
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2020.302
Subject(s) - crossover , genetic algorithm , mathematical optimization , dimension (graph theory) , population , constraint (computer aided design) , water resources , computer science , operator (biology) , irrigation , economic shortage , operations research , mathematics , ecology , artificial intelligence , biochemistry , chemistry , linguistics , demography , geometry , philosophy , repressor , sociology , government (linguistics) , transcription factor , gene , pure mathematics , biology
In order to distribute water resources reasonably, it is advantageous to make full use of resources and produce high economic and social benefits. Taking the Dujiangyan irrigation area of China as an example, we discuss the idea of establishing and solving the optimal allocation model of water resources. With this aim, a two-dimensional constraint model with highest economic value, minimum water shortage, minimum underground water consumption and necessary living water demand was established. In order to solve this model, we improved a multi-population genetic algorithm, extending the genetic optimization of the algorithm into two dimensions, taking population as the vertical dimension and the individual as the horizontal dimension, and transforming the cross genetic operator to copy the genetic (crossover) operator and the mutation operator to only act on the vertical dimension, so as to optimize the allocation of such discrete objectives of water resources in the irrigation area with a particular model suitable for the region. The distribution results successfully control the water shortage rate of each area at a low level, which saves the exploitation of groundwater to the maximum extent and produces high economic benefits. The improved algorithm proposed in this paper has a kind of strong optimization ability and provides a new solution for the optimization problem with multiple constraints.

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