guofei9987/scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
[](https://pypi.org/project/scikit-opt/) [](https://travis-ci.com/guofei9987/scikit-opt) [](https://codecov.io/gh/guofei9987/scikit-opt) [](https://github.com/guofei9987/scikit-opt/blob/master/LICENSE) [](https://github.com/guofei9987/scikit-opt/fork) [](https://pepy.tech/project/scikit-opt) [](https://github.com/guofei9987/scikit-opt/discussions) Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm, Artificial Fish Swarm Algorithm in Python) For the current developer version: UDF (user defined function) is available now! For example, you just worked out a new type of selection function. Now, your selection function is like this: -> Demo code: examples/demogaudf.py#s1 Import and build ga -> Demo code: examples/demogaudf.py#s2 Regist your udf to GA -> Demo code: examples/demogaudf.py#s3 scikit-opt also provide some operators -> Demo code: examples/demogaudf.py#s4 Now do GA as usual -> Demo code: examples/demogaudf.py#s5 For advanced users: -> Demo code: examples/demogaudf.py#s6 (New in version 0.3.6) Run an algorithm for 10 iterations, and then run another 20 iterations base on the 10 iterations before: see https://github.com/guofei9987/scikit-opt/blob/master/examples/examplefunctionmodes.py We are developing GPU computation, which will be stable on version 1.0.0 An example is already available: https://github.com/guofei9987/scikit-opt/blob/master/examples/demogagpu.py Step1:define your…
Read the full README ↗ · Preview checked 2026-10-27T23:31:48.384Z
Inside the original README — Document outline
- scikit-opt
- install
- Features
- Feature1: UDF
- feature2: continue to run
- feature3: 4-ways to accelerate
- feature4: GPU computation
- Quick start
- 1. Differential Evolution
- 2. Genetic Algorithm
- 2.2 Genetic Algorithm for TSP(Travelling Salesman Problem)
- 3. PSO(Particle swarm optimization)
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Links from the README
References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.
- ![License
- examples/demogaudf.py#s1
- examples/demogaudf.py#s2
- examples/demogaudf.py#s3
- examples/demogaudf.py#s4
- examples/demogaudf.py#s5
- examples/demogaudf.py#s6
- https://github.com/guofei9987/scikit-opt/blob/master/examples/examplefunctionmodes.py
- https://github.com/guofei9987/scikit-opt/blob/master/examples/demogagpu.py
- examples/demode.py#s1
- examples/demode.py#s2
- examples/demoga.py#s1
Documentation belongs to its respective authors. Reported project/model license: MIT. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
Repository facts
- Owner
- guofei9987
- Primary language
- Python
- Stars
- 6,724
- Forks
- 1,107
- Open issues + pull requests
- 77
- License
- MIT
- Archived
- No
- Default branch
- master
- Created
- 2017-12-05T10:20:41.000Z
- Last push
- 2026-03-25T09:12:13.000Z
Topics and intended use
Owner-supplied topics: ant-colony-algorithm, artificial-intelligence, fish-swarms, genetic-algorithm, heuristic-algorithms, immune, immune-algorithm, optimization, particle-swarm-optimization, pso, simulated-annealing, travelling-salesman-problem, tsp
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
Evaluate before installing
Review licensing and dependencies, inspect recent commits and unresolved issues, and test in an isolated environment before production use. Stars and forks alone cannot answer these questions.
Source and freshness
Source: GitHub. Metadata observed 2026-11-01T13:20:54.848Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
Related repositories
EbookFoundation/free-programming-books
donnemartin/system-design-primer