Skip to main content

Special Structure Detection for Pyomo

Project description

Special Structure Detection for Pyomo

DOI travis codecov

This library implements methods to:

  • Detect convex and concave expressions

  • Detect increasing and decreasing expressions

  • Detect linear, quadratic and polynomial expressions

  • Tighten expression bounds

Please reference this software as

@Article{Suspect2019,
author={Ceccon, Francesco and Siirola, John D. and Misener, Ruth},
title={{SUSPECT}: {MINLP} special structure detector for Pyomo},
journal={Optimization Letters},
year={2019},
month={Feb},
issn="1862-4480",
doi="10.1007/s11590-019-01396-y",
url="https://doi.org/10.1007/s11590-019-01396-y"
}

Documentation

Documentation is available at https://cog-imperial.github.io/suspect/

Installation

SUSPECT requires Python 3.5 or later. We recommend installing SUSPECT in a virtual environment

To create the virtual environment run:

$ python3 -m venv myenv
$ source myenv/bin/activate

Then you are ready to clone and install SUSPECT:

$ git clone https://github.com/cog-imperial/suspect.git
$ cd suspect
$ pip install -r requirements.txt
$ pip install .

Command Line Usage

The package contains an utility to display structure information about a single problem.

You can run the utility as:

model_summary.py -p /path/to/problem.osil

or, if you want to check variables bounds include the solution:

model_summary.py -p /path/to/problem.osil -s /path/to/problem.sol

The repository also includes a Dockerfile to simplify running the utility in batch mode in a cloud environment. Refer to the batch folder for more information.

Library Usage

from suspect import detect_special_structure
import pyomo.environ as aml


model = aml.ConcreteModel()
model.x = aml.Var()
model.y = aml.Var()

model.obj = aml.Objective(expr=(model.y - model.x)**3)
model.c1 = aml.Constraint(expr=model.y - model.x >= 0)

info = detect_special_structure(model)

# try info.variables, info.objectives, and info.constraints
print(info.objectives['obj'])

License

Copyright 2018 Francesco Ceccon

Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at:

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Acknowledgements

This work was funded by an Engineering & Physical Sciences Research Council Research Fellowship to RM [Grant Number EP/P016871/1].

Changelog

Next

1.1.0 (2019-01-31)

  • Add Quadratic expression type

  • Add Interval special case for x*x

  • Fix Interval sin

  • Add Interval comparison with numbers

1.0.7 (2018-08-30)

  • Add Interval abs

  • Add Interval power

1.0.6 (2018-07-05)

  • Change ExpressionType and UnaryFunctionType to IntEnum

1.0.5 (2018-07-05)

  • Documentation improvements

1.0.4 (2018-07-04)

  • First public release. Yay!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cog-suspect-1.5.5.tar.gz (68.9 kB view details)

Uploaded Source

File details

Details for the file cog-suspect-1.5.5.tar.gz.

File metadata

  • Download URL: cog-suspect-1.5.5.tar.gz
  • Upload date:
  • Size: 68.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.25.0 CPython/3.6.6

File hashes

Hashes for cog-suspect-1.5.5.tar.gz
Algorithm Hash digest
SHA256 b21db0026534ca9c80b49bd2095eeee7604dce29e3bd9d9d6de2802d89e6f2f8
MD5 cd9750aba0729a77a26e67bc1fca04f6
BLAKE2b-256 79aff25562769b6d54d89f11ad612783542c53eb46f4ddefe5b159c8353f13fb

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page