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| Nonlinear programming genetic algorithm in transient electromagnetic inversion |
| LI Feng-Ping, YANG Hai-Yan, LIU Xu-Hua, ZHAO Hai-Jiao |
| State Key Laboratory Breeding Base of Nuclear Resources and Environment, East China University of Technology, Nanchang 330013, China |
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Abstract The local search capability of the classical nonlinear programming algorithm is strong, and the genetic algorithm adopts the selection, crossover and mutation operators to perform the search, hence its global search capability is strong, whereas the local search capability of the genetic algorithm is weak. Therefore, a nonlinear programming genetic algorithm (NPGA) was proposed based on the previous studies, which combines the advantages of these two algorithms. Proved by function test, the proposed algorithm could significantly improve the search performance of genetic algorithm. On such a basis, the geoelectric models were established. Finally, the nonlinear programming genetic algorithm was applied to the inversion calculation of TEM. The results show that the proposed algorithm has fast convergence speed and high calculation precision, thus exhibiting good inversion effect.
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Received: 05 November 2016
Published: 10 April 2017
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