https://github.com/dschmitz89/ampgo

Adaptive memory programming for Global Optimization
https://github.com/dschmitz89/ampgo

global-optimization heuristic-search-algorithms nlopt nonlinear-optimization scipy tabu-search

Last synced: 3 months ago
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Adaptive memory programming for Global Optimization

• Host: GitHub
• URL: https://github.com/dschmitz89/ampgo
• Owner: dschmitz89
• Fork: true (andyfaff/ampgo)
• Created: 2021-08-08T10:12:40.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2021-09-01T19:57:48.000Z (over 3 years ago)
• Last Synced: 2024-09-27T09:37:39.127Z (3 months ago)
• Topics: global-optimization, heuristic-search-algorithms, nlopt, nonlinear-optimization, scipy, tabu-search
• Language: Python
• Homepage: https://ampgo.readthedocs.io/en/latest/index.html
• Size: 55.7 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ampgo

Global optimization via adaptive memory programming with a scipy.optimize like API.

## Installation

```bash

pip install ampgo

```

## Example: Minimizing the six-hump camelback function in ampgo

```python

import ampgo

def obj(x):

    """Six-hump camelback function"""

    x1 = x[0]

    x2 = x[1]

    f = (4 - 2.1*(x1*x1) + (x1*x1*x1*x1)/3.0)*(x1*x1) + x1*x2 + (-4 + 4*(x2*x2))*(x2*x2)

    return f

bounds = [(-5, 5), (-5, 5)]

res = ampgo.ampgo(obj, bounds)

print(res.x)

print(res.fun)

```

## Documentation

For the full API reference check out the [online documentation](https://ampgo.readthedocs.io/en/latest/index.html).

## History

Coded by Andrea Gavana, [email protected]. Original hosted at https://code.google.com/p/ampgo/.  Made available under the MIT licence. Usage and installation modified by Daniel Schmitz.

Differences compared to original version:

* Support all of SciPy's local minimizers

* Return a OptimizeResult class like SciPy's global optimizers

* Require bounds instead of starting point

* Jacobian and Hessian support

* Support all of NLopt's local minimizers (requires [simplenlopt](https://simplenlopt.readthedocs.io/en/latest/index.html))

* Drop support for OpenOpt solvers as OpenOpt has been stale for several years