Feasible Sequential Quadratic Programming for Finely Discretized Problems from SIP
A Sequential Quadratic Programming algorithm designed to efficiently solve nonlinear optimization problems with many inequality constraints, e.g. problems arising from finely discretized Semi-Infinite Programming, is described and analyzed. The key features of the algorithm are (i) that only a few of the constraints are used in the QP sub-problems at each iteration , and (ii) that every iterate satisfies all constraints.
KeywordsSearch Direction Line Search Accumulation Point Sequential Quadratic Programming Local Convergence
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