Abstract:The issue of static corrections is global optimum issue with multi-parameters and multi-extreme-values. The ordinary genetic algorithm (GA) almost certainly appears premature convergence when a great deal of unknown parameters exists and is difficult to ensure global convergence. For that reason, based on the Glover theory, the paper presented a strategy mixed GA with TS-TSGA. The new recomposed operator is constructed by introducing the TS-distinct memorial function into GA evolution searching process; in view of the disadvantages of poor GA climbing ability and premature, taking TS as catastrophe factor TSR of GA, i. e. using TS to conduct the catastrophe of GA in an adequate scale when GA is finished in local extreme values, that can both keep the GA-searched results and skip out the possible trap of local extreme values and the search can finally progress to global extreme value. The TSGA better solved complicated non-linear problem of residual statics computation by overcoming poor climbing ability of GA through using TS algorithm and integrating the advantages of multiple starting points of GA with good memorial function and strong climbing ability of TS. The processed results of modeling data showed the method in the paper has advantages of strong adaptability and fast converging to the optimum solution of larger statics, which is a practical approach computing statics in complex topographic conditions.
李辉峰, 邓飞, 周熙襄. 利用TS与GA的混合算法(TSGA)求取剩余静校正量[J]. 石油地球物理勘探, 2006, 41(3): 327-332.
Li Hui-feng, Deng Fei, Zhou Xi-xiang. Using hybrid algorithm (TSGA) of TS and GA for computation of residual statics. OGP, 2006, 41(3): 327-332.