pypop7

Contents of PyPop7:

  • Installation
  • User Guide
  • Online Tutorials
  • Evolution Strategies (ES)
  • Natural Evolution Strategies (NES)
  • Estimation of Distribution Algorithms (EDA)
  • Cross-Entropy Method (CEM)
  • Differential Evolution (DE)
  • Particle Swarm Optimizer (PSO)
  • Cooperative Coevolution (CC)
  • Simulated Annealing (SA)
  • Genetic Algorithms (GA)
  • Evolutionary Programming (EP)
  • Direct/Pattern Search (DS)
  • Random Search (RS)
  • Bayesian Optimization (BO)
  • Black-Box Optimization (BBO)
  • Benchmarking Functions for BBO
  • Util Functions for BBO
  • Development Guide
  • Applications
  • Sponsor
  • Design Philosophy
  • Changing Log
  • Software Summary
pypop7
  • Sponsor
  • View page source

Sponsor

This open-source Python library for large-scale black-box optimization (PyPop7) was supported by Shenzhen Fundamental Research Program (2000000 Yuan granted to Prof. Shi from Southern University of Science and Technology (SUSTech) @Shenzhen, China from 2021 to 2023), and actively developed by his group members (Qiqi Duan also in Harbin Institute of Technology, Chang Shao also in University of Technology Sydney, and Guochen Zhou also in Zhejiang University).

  • Now Yijun Yang from Tencent/University of Technology Sydney (UTS)/Beihang University helps to suggest papers about Bayesian Optimization (BO) and other new/advanced black-box optimizers (BBO).

  • Now Qi Zhao from SUSTech/University of New South Wales/Beijing University of Technology helps to proofread most online documents.

  • From 2024/5/1, Xingyu Zhou from SUSTech is added as one of core developers, in order to code and check new BBO mainly from the machine learning community.

  • From 2024, Yuwei Huang from SUSTech has been added as one of core developers, in order to increase new BBO mainly from the automatic control community.

  • From 2024, Yajing Tan from SUSTech has been added as one of core developers, in order to increase new BBO (e.g., SPSA).

  • From 2021, Mingyang Feng from University of Birmingham (UoB)/University of Electronic Science and Technology of China helped to search a number of papers involved in this library and test some code on MacOS X.

  • From 2023, Jian Zeng from Guangdong Police College/Harbin Institute of Technology helps to collect BBOs on data mining.

  • From 2022 to 2023, Zhuowei Wang from UTS helped to test some code on Linux and proofread some online documents.

  • In 2023, Minghan Zhang from University of Warwick/Imperial College London helped to search some papers involved in this library and test some code on MacOS X.

  • In 2023, Haobin Yang from SUSTech helped to proofread and standardize some online documents.

  • In 2023, Xianglong Chen from SUSTech helped to proofread and standardize some online documents.

  • In 2023, Zonghan He from SUSTech helped to test the installation process on Windows10 OS.

We also acknowledge the initial (2017) discussions with Hao Tong (when at SUSTech, now at UoB) and recent (2022) discussions wih Changwu Huang (at SUSTech).

Finally, we thank very much for all the following open-source code to make repeatability much easier (still updated now):

  • cyberagent.ai: PYTHON code for CMAES

  • Dr. Ilya Loshchilov: C code for LMCMA ( broken )

  • Dr. Ilya Loshchilov: C code for LMCMAES

  • Prof. Tobias Glasmachers: PYTHON code for LMMAES

  • Prof. Youhei Akimoto: PYTHON code for VDCMA

  • Prof. Xiaoyu He: MATLAB code for MMES ( forked )

  • Prof. Suganthan: MATLAB code for CLPSO ( forked )

https://visitor-badge.laobi.icu/badge?page_id=Evolutionary-Intelligence.pypop-sponsor
Previous Next

© Copyright 2021-2025, Evolutionary-Intelligence (Qiqi Duan) @ HIT & SUSTech.

Built with Sphinx using a theme provided by Read the Docs.