A new SQP algorithm and numerical experiments for nonlinear inequality constrained optimization problem

20140820 https://doi.org/10.14419/ijamr.v3i3.3121 
Abstract
In this paper, a new algorithm based on SQP method is presented to solve the nonlinear inequality constrained optimization problem. As compared with the other existing SQP methods, per single iteration, the basic feasible descent direction is computed by solving at most two equality constrained quadratic programming. Furthermore, there is no need for any auxiliary problem to obtain the coefficients and update the parameters. Under some suitable conditions, the global and superlinear convergence are shown.
Keywords: Global convergence, Inequality constrained optimization, Nonlinear programming problem, SQP method, Superlinear convergence rate.

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How to Cite
SohrabiHaghighat, M., & Ghasemi, M. (2014). A new SQP algorithm and numerical experiments for nonlinear inequality constrained optimization problem. International Journal of Applied Mathematical Research, 3(3), 336347. https://doi.org/10.14419/ijamr.v3i3.3121Received date: 20140705
Accepted date: 20140802
Published date: 20140820