Derivative-free and blackbox optimization Charles Audet, Warren Hare

Format:

Book

Author/Creator:

Audet, Charles, author.

Hare, Warren (Warren L.), 1975- author.

Series:

Springer series in operations research

Springer series in operations research and financial engineering 2197-1773

Language:

English

Subjects (All):

Mathematical optimization.

Numerical analysis.

Physical Description:

1 online resource

Edition:

Second edition

Place of Publication:

Cham, Switzerland Springer [2026]

Summary:

"The second edition of Derivative-Free and Blackbox Optimization offers a comprehensive introduction to the field of optimization when derivatives are unavailable, unreliable, or impractical. Whether you’re a student, instructor, or self-learner, this book is designed to guide you through both the foundations and advanced techniques of derivative-free and blackbox optimization. This new edition features significantly expanded exercises, updated and intuitive notation, over 30 new figures, and a wide range of pedagogical enhancements aimed at making complex concepts accessible and engaging. The book is structured into five parts. Part 1 established foundational principles, including an expanded chapter on proper benchmarking. Parts 2, 3, and 4, take an in-depth look at heuristics, direct search, and model based approaches (respectively). Part 5 extends these approaches to specialised settings. Finally, a new appendix contributed by Sébastien Le Digabel, details several real-world applications of blackbox optimization, and links to software for each application. Whether used in the classroom or for independent exploration, this book is a powerful resource for understanding and applying optimization methods – no gradients required"-- Springer Nature Link

Contents:

Introduction: tools and challenges in DFO BBO

Mathematical background

The beginnings of DFO algorithms

Comparing optimization methods

Genetic algorithms

Nelder-mead

Positive bases and nonsmooth optimization

Generalised pattern search

Mesh adaptive direct search

Variables and constraints

Assessing model quality

Simplex gradients and Hessians

Model-based descent

Model-based trust region

Optimization using surrogates and models

Biobjective optimization

Final remarks on DFO and BBO

Notes:

Includes bibliographical references and index

Online resource; title from PDF title page (Springer Nature Link, viewed June 22, 2026)

Other Format:

Print version Audet, Charles Derivative-free and blackbox optimization

ISBN:

9783032009067

3032009065

OCLC:

1596920721

Access Restriction:

Restricted for use by site license