In many optimization problems arising from scientific, engineering and artificial intelligence
applications, objective and constraint functions are available only as the output of a black …

In this paper, a target capacity based resource optimization (TC-RO) scheme is developed
for multiple target tracking (MTT) application in radar networks. The key idea of this scheme …

Abstract The late Professor MJD Powell devised five trust-region methods for derivative-free
optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully …

We introduce a general framework for large-scale model-based derivative-free optimization
based on iterative minimization within random subspaces. We present a probabilistic worst …

Derivative-free algorithms seek the minimum value of a given objective function without
using any derivative information. The performance of these methods often worsens as the …

We propose a simple yet effective method to perform surface remeshing with hard
constraints, such as bounding approximation errors and ensuring Delaunay conditions. The …

This thesis studies derivative-free optimization (DFO), particularly model-based methods
and software. These methods are motivated by optimization problems for which it is …

Derivative-free optimization methods are numerical methods for optimization problems in
which no derivative information is used. Such optimization problems are widely seen in …

We present a model-based derivative-free method for optimization subject to general convex
constraints, which we assume are unrelaxable and accessed only through a projection …

We propose a random-subspace algorithmic framework for global optimization of Lipschitz-
continuous objectives, and analyse its convergence using novel tools from conic integral …