Safe Zeroth-Order Optimization Using Linear Programs
Baiwei Guo (EPFL Switzerland)
Yang Wang (TU Delft - Team Riccardo Ferrari)
M Kamgarpour (EPFL Switzerland)
Giancarlo Ferrari-Trecate (EPFL Switzerland)
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Abstract
To solve unmodeled optimization problems with hard constraints, this paper proposes a novel zeroth-order approach called Safe Zeroth-order Optimization using Linear Programs (SZO-LP). The SZO-LP method solves a linear program in each iteration to find a descent direction, followed by a step length determination. We prove that, under mild conditions, the iterates of SZO- LP have an accumulation point that is also the primal of a KKT pair. We then apply SZO-LP to solve an Optimal Power Flow (OPF) problem on the IEEE 30-bus system. The results demonstrate that SZO-LP requires less computation time and samples compared to state-of-the-art approaches.