The large scale nonlinear optimization has become a research focus in the planning, the interior-point algorithm is an effective method for solving large-scale inequality constraints, however most of the filter interior-point algorithm only consider the feasibility and stability, ignoring the adjuvant on the performance of algorithm, so that in this paper, in the light of the Karush-Kuhn-Tucker (KKT) conditions of the interior-point algorithm, a new algorithm, with feasibility, auxiliary and stability as the objective of the search step, use the amount of the violation of equality constraints, the obstacle objective function and auxiliary conditions as a filter option to calculate the search step and build a computer simulation environment for the numerical test, compared with the basic filter method from the number of iterations, function estimated times and run time. The test results show that under the same conditions the new algorithm, compared with the basic filter method, can get more search steps, and achieve fast convergence, having good global convergence, robustness and effectiveness.
SONG Yi;YANG Caixia;WEI Nini
. Research and Simulation on the Triple-objective Filter Optimization Algorithm Based on Interior point Algorithm[J]. Science & Technology Review, 2013
, 31(1)
: 62
-65
.
DOI: 10.3981/j.issn.1000-7857.2013.01.010