Caution: The signatures of the Python and MATLAB functions change in PDFO 2.0. Check the changelog.

PDFO documentation#

Version:

2.1

Downloads:

103,732

Author of solvers:

M. J. D. Powell

Authors of PDFO:

Tom M. Ragonneau | Zaikun Zhang

PDFO is a cross-platform package providing the late Professor M. J. D. Powell’s derivative-free (i.e., zeroth-order) optimization solvers. Using only function values, but not derivatives, it solves problems of the form

\[\begin{split}\min_{x \in \R^n} \quad \obj ( x ) \quad \text{s.t.} \quad \begin{cases} \xl \le x \le \xu,\\ \aub x \le \bub, ~ \aeq x = \beq,\\ \cub ( x ) \le 0, ~ \ceq ( x ) = 0. \end{cases}\end{split}\]

To install PDFO for Python, run in your terminal

pip install pdfo

You can also check the installation guide for MATLAB. For more details, see the user guide.

Citing PDFO#

If you would like to acknowledge the significance of PDFO in your research, we suggest citing the project as follows:

The corresponding BibTeX entry is given hereunder.

@unpublished{pdfo,
    author       = {Ragonneau, T. M. and Zhang, Z.},
    title        = {{PDFO}: a cross-platform package for {P}owell's derivative-free optimization solvers},
    eprint       = {2302.13246},
    eprinttype   = {arxiv},
    eprintclass  = {math.OC},
    year         = 2023,
    doi          = {10.48550/arXiv.2302.13246},
}

Statistics#

As of April 17, 2024, PDFO has been downloaded 103,732 times, including

The following figure shows the cumulative downloads of PDFO.

(Source code, png, hires.png, pdf)

_images/index-1.png

We started tracking the downloads of PDFO on Anaconda on October 2022. The API we employ to track the downloads of PDFO on Anaconda only provides the cumulative downloads. Therefore, we do not know when the downloads of PDFO on Anaconda have been made. In this plot, all of them are assumed to have been made on October 2022.

Acknowledgments#

PDFO is dedicated to the memory of the late Professor M. J. D. Powell with gratitude for his inspiration and for the treasures he left to us. We are grateful to Professor Ya-xiang Yuan for his everlasting encouragement and support.

The development of PDFO is a long-term project, which would not be sustainable without the continued funds from the Hong Kong Research Grants Council (ref. PolyU 253012/17P, PolyU 153054/20P, and PolyU 153066/21P), the Hong Kong PhD Fellowship Scheme (ref. PF18-24698), and The Hong Kong Polytechnic University (PolyU), in particular the Department of Applied Mathematics (AMA).