JING S J, DUAN X H, NIU H F.A filled function algorithm for solving nonlinear global optimization problems[J].Journal of Henan Polytechnic University(Natural Science) ,2022,41(6):169-173.

doi:10.16186/j.cnki.1673-9787.2020100055

Received:2020/10/23

Revised:2021/03/10

Published:2022/11/25

A filled function algorithm for solving nonlinear global optimization problems

JING Shujie, DUAN Xiaohui, NIU Haifeng

School of Mathematics and Information Science，Henan Polytechnical University，Jiaozuo 454000，Henan，China

Abstract:Since the filled function is a composite function of the objective function，the corresponding filled function becomes more complex when the objective function is complex.In addition，the more parameters are contained in the filled function，the more difficult it is to adjust during calculation，which will increase the amount of calculation.To solve this problem，a continuously differentiable single parameter filled function was proposed under the condition of no inequality constraints，and the related properties of the function were discussed theoretically.By minimizing the filled function，the current local minimum could be jumped out and a better local minimum could be found.Finally，a new filled algorithm was designed combining SQP algorithm and BFGS algorithm，and examples were selected for numerical experiments.The calculation results showed that the algorithm was effective and feasible was provided，and an efficient filled function algorithm with simple form and easy adjustment of parameters for solving nonlinear global optimization problems.

Key words:filled function;nonlinear global optimization;local minimizer

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