Online Optimization Using Zeroth Order Oracles

Iman Shames*, Daniel Selvaratnam, Jonathan H. Manton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


This letter considers the iterative numerical optimization of time-varying cost functions where no gradient information is available at each iteration. In this case, the proposed algorithm estimates a directional derivative by finite differences. The main contributions are the derivation of error bounds for such algorithms and proposal of optimal algorithm parameter values, e.g., step-sizes, for strongly convex cost functions. The algorithm is applied to tackle a source localization problem using a sensing agent where the source actively evades the agent. Numerical examples are provided to illustrate the theoretical results.

Original languageEnglish
Article number8733040
Pages (from-to)31-36
Number of pages6
JournalIEEE Control Systems Letters
Issue number1
Publication statusPublished - Jan 2020
Externally publishedYes


Dive into the research topics of 'Online Optimization Using Zeroth Order Oracles'. Together they form a unique fingerprint.

Cite this