The optimization of many engineering design problems requires a nonlinear programming algorithm that is robust, efficient, and feasible at intermediate iterations. Based on the strengths of the generalized reduced gradient (GRG) and sequential quadratic programming (SQP) algorithms, a hybrid SQP-GRG algorithm is developed. The hybrid algorithm uses the SQP search direction and a modified GRG line search. The resulting SQP-GRG algorithm is shown to be robust, feasible at intermediate iterations, and comparable in efficiency to Powell’s SQP algorithm on 26 test problems.

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