PDFO: a cross-platform package for Powell's derivative-free optimization solvers

TM Ragonneau, Z Zhang - Mathematical Programming Computation, 2024 - Springer
Abstract The late Professor MJD Powell devised five trust-region methods for derivative-free
optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully …

[图书][B] Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation and Perspectives

C Cartis, NIM Gould, PL Toint - 2022 - SIAM
Do you know the difference between an optimist and a pessimist? The former believes we
live in the best possible world, and the latter is afraid that the former might be right.… In that …

Scalable subspace methods for derivative-free nonlinear least-squares optimization

C Cartis, L Roberts - Mathematical Programming, 2023 - Springer
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 …

Model-based derivative-free optimization methods and software

TM Ragonneau - arXiv preprint arXiv:2210.12018, 2022 - arxiv.org
This thesis studies derivative-free optimization (DFO), particularly model-based methods
and software. These methods are motivated by optimization problems for which it is …

New subspace method for unconstrained derivative-free optimization

M Kimiaei, A Neumaier, P Faramarzi - ACM Transactions on …, 2023 - dl.acm.org
This article defines an efficient subspace method, called SSDFO, for unconstrained
derivative-free optimization problems where the gradients of the objective function are …

Cooperative coevolution for non-separable large-scale black-box optimization: Convergence analyses and distributed accelerations

Q Duan, C Shao, G Zhou, H Yang, Q Zhao, Y Shi - Applied Soft Computing, 2024 - Elsevier
Given the ubiquity of non-separable optimization problems in real worlds, in this paper we
analyze and extend the large-scale version of the well-known cooperative coevolution (CC) …

Zonewise surrogate-based optimization of box-constrained systems

SV Srinivas, IA Karimi - Computers & Chemical Engineering, 2024 - Elsevier
Complex physical or numerical systems may exhibit distinct behaviors in various zones of
their design spaces. We present an algorithm that uses multiple cluster-based surrogates for …

OPM, a collection of optimization problems in Matlab

S Gratton, PL Toint - arXiv preprint arXiv:2112.05636, 2021 - arxiv.org
arXiv:2112.05636v1 [math.OC] 10 Dec 2021 Page 1 arXiv:2112.05636v1 [math.OC] 10 Dec
2021 OPM, a collection of Optimization Problems in Matlab S. Gratton∗ and Ph. L. Toint† 6 XII …

An improved randomized algorithm with noise level tuning for large-scale noisy unconstrained DFO problems

M Kimiaei - Numerical Algorithms, 2025 - Springer
In this paper, a new randomized solver (called VRDFON) for noisy unconstrained derivative-
free optimization (DFO) problems is discussed. Complexity result in the presence of noise for …

Distributed Evolution Strategies with Multi-Level Learning for Large-Scale Black-Box Optimization

Q Duan, C Shao, G Zhou, M Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the post-Moore era, main performance gains of black-box optimizers are increasingly
depending on parallelism, especially for large-scale optimization (LSO). Here we propose to …