Open AccessOptimal allocation of water resources through artificial fish swarm algorithm: A case study in Haixing, China
Author(s) -
M Y Liu,
Qinghua Luan,
M Liu,
Aixi Gong,
Hao Hu
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/344/1/012054
Subject(s) - water resources , swarm behaviour , resource allocation , particle swarm optimization , resource (disambiguation) , water scarcity , china , optimal allocation , computer science , fish <actinopterygii> , natural resource , operations research , water resource management , mathematical optimization , environmental science , fishery , algorithm , ecology , geography , engineering , mathematics , artificial intelligence , biology , computer network , archaeology
North China is a typical developing region where the conflict between large water demand and little natural water resources exist. Thus, scientifically optimizing the allocation of regional water resources is particularly significant in this area. In this study, Haixing County, China was selected as the research region. Then, regional optimization model of water resource allocation was established, of which the objective function aims at the maximum integrated benefit of regional social and economy. In this model, two forbidden red lines of water use amount and water use efficiency were considered as the constraints, and Artificial Fish Swarm Algorithm was applied to calculate the optimization of water resource allocation. In 2020, the p = 50% total water shortage is forecast as 0.747 × 10 6 m 3 or 2.1%. The results show that the efficiency and benefits have been improved, which illustrates that the optimization allocation of water resources through Artificial Fish Swarm Algorithm is reasonable. The research could provide a crucial technical support for regional water resource management.