Expected complexity analysis of stochastic direct-search

DOI10.1007/s10589-021-00329-9zbMath1484.90054arXiv2003.03066OpenAlexW3214921798MaRDI QIDQ2070336

Kwassi Joseph Dzahini

Publication date: 24 January 2022

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2003.03066

zbMATH Keywords

stochastic optimizationstochastic processesconvergence ratederivative-free optimizationblackbox optimizationdirect-search

Mathematics Subject Classification ID

Abstract computational complexity for mathematical programming problems (90C60) Derivative-free methods and methods using generalized derivatives (90C56) Stochastic programming (90C15)

Related Items (2)

A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning ⋮ Constrained stochastic blackbox optimization using a progressive barrier and probabilistic estimates

Cites Work

• Unnamed Item
• Stochastic derivative-free optimization using a trust region framework
• Worst case complexity of direct search
• Stochastic optimization using a trust-region method and random models
• Stochastic mesh adaptive direct search for blackbox optimization using probabilistic estimates
• Convergence of Trust-Region Methods Based on Probabilistic Models
• Introduction to Derivative-Free Optimization
• Analysis of Generalized Pattern Searches
• Derivative-Free and Blackbox Optimization
• Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise
• A Stochastic Line Search Method with Expected Complexity Analysis
• Mesh Adaptive Direct Search Algorithms for Constrained Optimization
• Direct Search Based on Probabilistic Descent
• Probability
• A basic course in probability theory

This page was built for publication: Expected complexity analysis of stochastic direct-search