A feasible trust-region algorithm for inequality constrained optimization

Yehui Peng

doi:10.1016/j.amc.2005.04.080

A feasible trust-region algorithm for inequality constrained optimization

2006-02-01

5

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AI

DOI：10.1016/j.amc.2005.04.080

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The paper presents an algorithm for smooth nonlinearly inequality constrained optimization problems, in which a sequence of feasible iterates is generated by a trust-region sequential quadratic programming subproblem at each iteration. Because of retaining feasibility, the objective function can be used as a merit function and the subproblems are feasible. Under common assumptions, the algorithm is globally convergent. The numerical results show it is promising. (c) 2005 Elsevier Inc. All rights reserved.

Keyword:

inequality constrained optimization

feasible trust-region algorithm

globally convergent

KKT point

SQP

A feasible trust-region algorithm for inequality constrained optimization

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