Change Log

Stable Releases (for users)

Release 1.8 (2022-6-5)

pip install neorl==1.8
  • Improvements in mixed-discrete optimization for various algorithms.

  • Introducing new ensemble optimization algorithms: AEO, EPSO, EDEV, HCLPSO.

  • New features for simulated annealing.

  • More organized documentation with subsections.

  • Application of NEORL to nuclear microreactors, recently published here:

Release 1.7 (2021-11-24)

pip install neorl==1.7
  • Fixed a major bug following scikit-learn update to 1.0.0. Now, NEORL supports scikit-learn <= 0.24.0

  • Misc. minor updates for the documentation and the source code

Release 1.6 (2021-09-10)

pip install neorl==1.6
  • The first NEORL stable release.

  • Includes all changes in all previous beta releases: 1.2.0b-1.5.7b.

  • Summary: 28 algorithms, 4 tuning methods, 10 real-world examples, and 39 unit tests.

  • Documentation and Github repo are up-to-date.

Beta Releases (for developers)

Release 1.7.8b (2022-6-4)

pip install neorl==1.7.8b --extra-index-url
  • Fixed bug related to protobuf <= 3.20 version to avoid tensorflow error when installation.

Release 1.7.7b (2022-6-4)

pip install neorl==1.7.7b --extra-index-url
  • Fixed bugs when initializing methods (ES, PSO, GWO, etc.) for discrete/mixed optimization with the argument x0.

  • Fixed bugs in TS, CS, SA for discrete/mixed optimization.

  • Enabled discrete/mixed optimization for AEO.

Release 1.7.6b (2022-4-25)

pip install neorl==1.7.6b --extra-index-url
  • Added a new features for parallel simulated annealing (PSA).

  • PSA features include new equilibrium schedule and new solution enforcement.

Release 1.7.5b (2022-3-29)

pip install neorl==1.7.5b --extra-index-url
  • Added a full module for EPSO with parallel support and all space types.

  • Fixed a minor bug in HCLPSO.

Release 1.7.4b (2022-3-26)

pip install neorl==1.7.4b --extra-index-url
  • Added a full module for HCLPSO with parallel support and all space types.

  • Added a full module for EDEV with parallel support and all space types.

Release 1.7.3b (2022-3-6)

pip install neorl==1.7.3b --extra-index-url
  • Fixed a division by zero bug for PSO mode globw.

  • Added a first test module for a new hybrid algorithm AEO (Aniormphic Ensemble Optimization).

  • Added documentation for AEO on the website.

Release 1.7.2b (2022-1-17)

pip install neorl==1.7.2b --extra-index-url
  • Fixed a plotting bug in NEORL benchmarks.

  • Added last_pop results to the returned history dictionary of ACO, SSA, JAYA, BAT, CS, XNES.

  • Allowed passing annealing parameters via **kwargs to WOA, GWO, PSO, MFO, HHO (this is for AEO ensemble research).

Release 1.7.1b (2022-1-03)

pip install neorl==1.7.1b --extra-index-url
  • Added new NEORL example 11 on nuclear microreactor application.

  • Documentation structure updates. Now subsections are part of the documentation structure.

Release 1.6.2b (2021-10-07)

pip install neorl==1.6.2b --extra-index-url
  • Removed summary files from RL runners.

  • Added a capability to save current model for RL runners. Currently best model and last model are saved.

Release 1.6.1b (2021-09-20)

pip install neorl==1.6.1b --extra-index-url
  • Fixed a bounding check bug in FNEAT and RNEAT.

  • Fixed different typos in the documentation.

  • Increased the width of the online documentation page to fit more code/words.

Releases 1.5.3b-1.5.7b (2021-09-10)

pip install neorl==1.5.7b --extra-index-url
  • Added hybrid neuroevolution algorithm: Neural genetic algorithm (NGA)

  • Added hybrid neuroevolution algorithm: Neural Harris hawks optimization (NHHO)

  • Added Cuckoo Search with all spaces handled.

  • Added Ant Colony optimization for continuous domains.

  • Added Tabu Search for discrete domains.

  • Fixed a critical bug in the terminal API in the followup 1.5.4b

  • Fixed a bug in the terminal API continue mode in the followups 1.5.5b-1.5.6b.

  • Fixed hyperthreading issue for RL algorithms in the followup 1.5.7b.

Release 1.5.2b (2021-08-10)

pip install neorl==1.5.2b --extra-index-url
  • Added hybrid neuroevolution algorithm PPO-ES.

  • Added hybrid neuroevolution algorithm ACKTR-DE.

  • Updated documentation for RL algorithms.

Release 1.5.1b (2021-08-01)

pip install neorl==1.5.1b --extra-index-url
  • Added RNEAT and FNEAT with full documentation.

  • Added mixed discrete optimization to WOA, GWO, SSA, DE, MFO, JAYA, PESA2

  • Added friendly implementation to construct parallel environments for RL: DQN, ACKTR, A2C, PPO

Release 1.5.0b (2021-07-28)

pip install neorl==1.5.0b --extra-index-url
  • Updated Example 1 on using RL to solve Travel Salesman problem

  • Added Example 10 on using RL to solve Knapsack problem

  • Added CEC-2008 benchmark functions for large-scale optimization

Release 1.4.8b (2021-07-14)

pip install neorl==1.4.8b --extra-index-url
  • Added environment class constructor for DQN, ACER, PPO, ACKTR, A2C

  • Added mixed discrete/continuous optimization for PPO, ACKTR, A2C

  • Added categorical/discrete optimization for ACER, DQN.

Releases 1.4.6b-1.4.7b (2021-07-09)

pip install neorl==1.4.7b --extra-index-url
  • Modifying Bat algorithm to handle mixed spaces.

  • Added Example 6 on three-bar truss design.

  • Added Examples 7 and 8 on pressure vessel design.

  • Added Example 9 on cantilever stepped beam.

  • Fixing bugs after 1.4.6b.

Releases 1.4.1b-1.4.5b (2021-07-05)

pip install neorl==1.4.5b --extra-index-url
  • Fixing bounding issues in most evolutionary algorithms.

  • Fixing PESA/PESA2 parallel mode.

  • Replacing XNES with WOA in modern PESA2.

  • Added a module for Harris Hawks Optimization.

  • Added the BAT algorithm.

  • Removed deprecation warnings of Tensorflow from NEORL.

  • Added a module for JAYA.

  • Added a module for MFO.

Old Releases (outdated)

Release 1.4.0b (2021-05-15)

  • Added a module for Simulated Annealing (SA).

  • Added a Genetic/Evolutionary hyperparameter tuning module.

  • Added ACER module for RL optimization.

  • Added ACKTR module for RL optimization.

  • Added a WOA module for evolutionary optimization.

  • Added a SSA module for evolutionary optimization.

Release 1.3.5b (2021-05-10)

  • Added CEC’2017 Test Suite benchmarks

  • Added a set of classical mathematical functions

  • Added new Example (4) on the website on how to access the benchmarks

  • Added new Example (5) on the website on how to optimize the benchmarks

Releases 1.3.1b-1.3.2b (2021-05-4)

  • Fixing miscellaneous bugs

Release 1.3.0b (2021-05-1)

  • Added a module for the hybrid algorithm PESA.

  • Added a module for the modern hybrid algorithm PESA2.

  • Added a GWO module.

  • Adding min/max modes for all algorithms.

Release 1.2.0b (2021-04-15)

  • The first public open-source version of NEORL

  • Added DE with serial implementation.

  • Added XNES with parallel implementation.

  • Restructuring the input parameter space.

  • Detailed README file in the Github page.

  • Added unit tests to NEORL.

  • Automatic documentation via Sphinx

Release 1.1.0-Private (2020-12-15)

  • Added Bayesian hyperparameter tuning from scikit-optimise.

  • Added parallel evolutionary strategies(ES).

  • Updated documentation.

Release 1.0.0-Private (2020-09-15)

  • Added evolutionary strategies ES.

  • Added a local PDF documentation.

  • Added parallel PSO.

  • Added Random search hyperparameter tuning.

Release 0.1.1-Private (2020-03-15)

  • A support for both classical (evolutionary) and modern (machine learning) optimization in the same package. Currently, DQN (serial), PPO (parallel), A2C (parallel), GA (serial), SA (serial) are supported. All RL algorithms are based upon stable-baselines.

  • Easy-to-use syntax and friendly interaction with the package.

  • A support for parallel computing.

  • Added grid search hyperparameter tuning.

  • For developers: an organized implementation and source code structure to facilitate the job of future external contributors.

  • NEORL examples are provided in the “examples” directory.