Liuqing Ye
Abstract
In this paper,the new SQP feasible descent algorithm for nonlinear constrained optimization problems presented,and under weaker conditions of relative,we proofed the new method still possesses global convergence and its strong convergence.The numerical results illustrate that the new methods are valid.
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In this paper,the new SQP feasible descent algorithm for nonlinear constrained optimization problems presented,and under weaker conditions of relative,we proofed the new method still possesses global convergence and its strong convergence.The numerical results illustrate that the new methods are valid.
Key concepts: Sequential quadratic programming, Convergence (economics), Mathematical optimization, Descent (aeronautics), Mathematics, Constrained optimization, Nonlinear programming, Nonlinear system