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math.OC2026
An objective-function-free algorithm for nonconvex stochastic optimization with deterministic equality and inequality constraints
S. Gratton, Ph. L. Toint
An algorithm is proposed for solving optimization problems with stochastic objective and deterministic equality and inequality constraints. This algorithm is objective-function-fre…
math.OC2026
An objective-function-free algorithm for general smooth constrained optimization
S. Bellavia, S. Gratton, B. Morini +1
A new algorithm for smooth constrained optimization is proposed that never computes the value of the problem's objective function and that handles both equality and inequality cons…
math.OC2026
Iteration complexity of the Difference-of-Convex Algorithm for unconstrained optimization: a simple proof
Serge Gratton, Philippe L. Toint
We propose a simple proof of the worst-case iteration complexity for the Difference of Convex functions Algorithm (DCA) for unconstrained minimization, showing that the global rate…