A unified convergence theory for Non monotone Direct Search Methods (DSMs) with extensions \ to DFO with mixed and categorical variables

This paper presents a unified convergence theory for non monotonous Direct Search Methods (DSMs), which embraces several algorithms that have been proposed for the solution of unconstrained and boxed constraints models. This paper shows that these models can be theoretically solved with the same methodology and under the same weak assumptions. All proofs have a … Read more

Unified approach for solving Box-Constrained models with continuous or discrete variables by Non monotonous Derivative Free Optimization techniques.

This paper describes a unified approach for solving Box-Constrained Optimization Problems (BCOP) in Euclidian spaces. The variables may be either continuous or discrete; in which case, they range on a grid of isolated points regularly spaced. For the continuous case, convergence is shown under standard assumptions; for the discrete case, slight modifications ensure that the … Read more