Acta Geodaetica et Cartographica Sinica (Jun 2016)

Ill-conditioned Problems Robust Solution of Improved Fruit Fly Optimization Algorithm Combining with Tikhonov Regularization Method

  • FAN Qian,
  • ZHANG Ning

Journal volume & issue
Vol. 45, no. 6
pp. 670 – 676


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Based on deeply analysis for optimization process of basic fruit fly optimization algorithm, an improved fruit fly optimization (IFOA) algorithm is proposed via changing random search direction and adding to a tuning coefficient of search radius. Moreover, through introducing the regularization term of objective function in IFOA algorithm, a new method that IFOA algorithm is combined with Tikhonov regularization method is put forward in order to resolving ill-conditioned problems. Analysis results of practical example show that solution accuracy of new method is superior to genetic algorithm and single Tikhonov regularization method. When observation contains gross errors, the deviation between the results and the true value will increase rapidly using least square method to solve ill-conditioned problems. At this time, the new method has strong robustness. Compared with intelligent search method represented by genetic algorithm, new method has the characteristics of less parameter, fast calculation speed, simple optimization process. It is more practical in ill-conditioned problems solution.