期刊
MATHEMATICAL PROGRAMMING
卷 122, 期 1, 页码 155-196出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s10107-008-0244-7
关键词
Nonlinear optimization; Equality constraints; Numerical algorithms; Global convergence
类别
资金
- Chinese Academy of Sciences [ICNAO2006]
- CERFACS (Toulouse)
- EPSRC [EP/F005369/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/F005369/1] Funding Source: researchfish
A new method is introduced for solving equality constrained nonlinear optimization problems. This method does not use a penalty function, nor a filter, and yet can be proved to be globally convergent to first-order stationary points. It uses different trust-regions to cope with the nonlinearities of the objective function and the constraints, and allows inexact SQP steps that do not lie exactly in the nullspace of the local Jacobian. Preliminary numerical experiments on CUTEr problems indicate that the method performs well.
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