Hello,

I'm using NLOpt to solve a (strictly convex) QP problem with box, linear and
quadratic inequality constraints. I tried the MMA and SLSQP methods. In most
cases, they both converge to a very good solution but SLSQP always gives an
answer that satisfies the inequality constraints up to required precision,
whereas MMA occasionally starts erring into the infeasible region (despite
starting with a feasible point). Did I misunderstand the strict requirement of
feasibility of NLOpt ? (I can send an example .c file if that helps).

I'm no optimisation expert and I'm particularly interested in the guarantee of
convergence of MMA. Are there similar results for the SLSQP method ?

thanks
Christophe






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