@article{Xu2026, 
author = {Jin Xu and Mengtian Wu and Kai Li and Lingling Wang and Hai Zhu and Minghui Wang},
title = {Groundwater contaminant source information identification based on tabu search and particle swarm optimization algorithm},
year = {2026},
journal = {Journal of Hohai University (Natural Sciences)},
volume = {54},
number = {1},
pages = {36-42},
keywords = {groundwater contaminant, information identification, optimization algorithm, tabu search, particle swarm optimization algorithm},
url = {https://www.sciopen.com/article/10.3876/j.issn.1000-1980.2026.01.005},
doi = {10.3876/j.issn.1000-1980.2026.01.005},
abstract = {To accurately identify key information such as the groundwater contaminant source location and contaminant release process, the simulation-optimization theoretical framework was used. The groundwater inversion problem that requires simultaneous identification of information from multiple contaminant sources was generalized as a mixed-variable optimization problem involving discrete and continuous variables. A two-stage combinatorial optimization algorithm based on tabu search and particle swarm optimization (TS-PSO) algorithm was proposed. The algorithm applied the tabu search method to locate contaminant sources and then used the particle swarm optimization algorithm to determine the contaminant release intensity and process. The verification results of the numerical examples show that compared with traditional evolutionary algorithms (GA and PSO algorithm), TS-PSO algorithm has higher solution efficiency, more reliable calculation results, and higher calculation accuracy. For the inversion problem of multiple contaminant sources, TS-PSO algorithm can quickly and effectively identify the location of contaminant sources, as well as the release intensity and release process of contaminants.}
}