• Corpus ID: 14277904

PuLP : A Linear Programming Toolkit for Python

@inproceedings{Mitchell2011PuLPA,
  title={PuLP : A Linear Programming Toolkit for Python},
  author={Stuart Mitchell and Michael J. O'Sullivan and Iain Dunning},
  year={2011}
}
This paper introduces the PuLP library, an open source package that allows mathematical programs to be described in the Python computer programming language. PuLP is a high-level modelling library that leverages the power of the Python language and allows the user to create programs using expressions that are natural to the Python language, avoiding special syntax and keywords wherever possible. 

ChemPy: A package useful for chemistry written in Python

ChemPy is a Python library that provides functions and classes for solving chemistry related problems and collects parametrizations of chemical properties of substances from the literature.

NLP.py: An object-oriented environment for large-scale optimization

NLP.py is a programming environment to model continuous optimization problems and to design computational methods in the high-level and powerful Python language with performance-critical parts

A brief introduction to LENSOLVER as linear programming application

This paper introduces LENSOLVER, as an application of linear programming application, developed based on the PuLP framework, which has a limitation of not supporting non-linear optimization.

Computing in Operations Research Using Julia

This paper explores how Julia, a modern programming language for numerical computing that claims to bridge this divide by incorporating recent advances in language and compiler design, can be used for implementing software and algorithms fundamental to the field of operations research, with a focus on mathematical optimization.

GBOML: Graph-Based Optimization Modeling Language

The Graph-Based Optimization Modeling Language (GBOML) is a modeling language for mathematical programming enabling the easy implementation of a broad class of structured mixed-integer linear

pyomo.dae: a modeling and automatic discretization framework for optimization with differential and algebraic equations

Pyomo.dae is an open source Python-based modeling framework that enables high-level abstract specification of optimization problems with differential and algebraic equations, providing a high degree of modeling flexibility and the ability to express constraints that cannot be easily specified in other modeling frameworks.

Parallel Algebraic Modeling for Stochastic Optimization

We present scalable algebraic modeling software, StochJuMP, for stochastic optimization as applied to power grid economic dispatch. It enables the user to express the problem in a high-level

Travelling salesman problem modelling by mixed interger linear programming of python (MIP)

  • Hanh Pham My
  • Computer Science
    Dong Thap University Journal of Science
  • 2022
The result shows that with small input data the modelling code of MIP executing quickly and converging to optimal value, while large scale input data require plenty of computation time; thereby algorithm improvement as well as parallel implementation are suggested.

GEKKO Optimization Suite

The GEKKO Optimization Suite is introduced,GEKKO’s approach and unique place among AMLs and optimal control packages are presented, and several examples of problems that are enabled by the GEKKo library are cited.

spopt: a python package for solving spatial optimization problems in PySAL

1 Center for Geospatial Sciences, University of California Riverside 2 Department of Geography and Environmental Sustainability, University of Oklahoma 3 Federal University of Viçosa 4 Oak Ridge
...

References

SHOWING 1-10 OF 10 REFERENCES

Python Optimization Modeling Objects (Pyomo)

We describe Pyomo, an open-source tool for modeling optimization applications in Python. Pyomo can be used to define abstract problems, create concrete problem instances, and solve these instances

Python Reference Manual

This reference manual describes the syntax and ``core semantics'' of the Python language, which is terse, but attempts to be exact and complete.

Selected Topics in Column Generation

The growing understanding of the dual point of view is emphasized, which has brought considerable progress to the column generation theory and practice, and is an ever recurring concept in "selected topics."

Python Package Index

  • Python Package Index

https://projects.coin-or.org/Coopr

  • https://projects.coin-or.org/Coopr

Dippy. https://projects.coin-or.org/ CoinBazaar/wiki/Projects/Dippy

  • Dippy. https://projects.coin-or.org/ CoinBazaar/wiki/Projects/Dippy

PEP 8 – Style Guide for Python Code

  • PEP 8 – Style Guide for Python Code

Open Source Iniatitive. MIT license

  • Open Source Iniatitive. MIT license

Python Standard Library. http://docs.python.org/library

  • Python Standard Library. http://docs.python.org/library

Cbc. http://www.coin-or.org

  • Cbc. http://www.coin-or.org