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README-Win.md

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1. Prerequisite: Install Anaconda Python 3.7

  1. Go to Anaconda Individual Edition site: https://www.anaconda.com/products/individual
  2. Download the 64-Bit Graphical Installer
  3. Run downloaded '.exe' file and follow Anaconda installation instructions.

2. Optional: Install CPlex

  • You can get a free Community Edition of CPLEX Optimization Studio, with limited solving capabilities in term of problem size.

  • Faculty members, research professionals at accredited institutions can get access to an unlimited version of CPLEX through the IBM® Academic Initiative.

3. Prerequisite: Get code from Github

That is, get this repo.

  1. cd SCLPsolver

4. Prerequisite: Set up an Anaconda environment

An Anaconda environment will allow you to install packages and configure Python for running SCLP. You can activate/deactivate the environment whenever you like, so that the SCLP setup is contained to this project.

  1. Optional: create an Anaconda environment conda create --name SCLP python=3.7
  2. Optional: activate the environment conda activate SCLP

5. Install Microsoft C++ Build Tools

  1. Go to Microsoft C++ Build Tools site: https://visualstudio.microsoft.com/visual-cpp-build-tools/
  2. Download and install Microsoft C++ Build Tools

6. Prerequisite: Install required packages

  1. Use conda installer. conda install --yes --file sclp_requirements.txt
  2. If you want to run the Design of Experiments, and you have CPLEX installed, install the CPLEX installer PIP installer pip install -r doe/cplex_integration/cplex_requirements.txt. Note: as of this writing, you cannot use conda install for the doopl package.

7. Compile cython files

Note: there is now a script for Windows that compiles and runs all of the below steps.

  1. cythonize.bat

Or do it manually:

  1. cd subroutines/equation_tools
  2. python setup.py build_ext --inplace
  3. cd ../lp_tools
  4. python setup.py build_ext --inplace
  5. cd ../state_tools
  6. python setup.py build_ext --inplace

8. Optional: run doe tests

  1. cd tests
  2. Generate random re-entrant line problem and solve it using simplex-type algorithm and CPLEX discretization. Note: if you have no CPLEX you should comment all starting from line 70 to the end of the file
    python simple_reentrant_test.py
  3. Generate random MCQN problem and solve it using simplex-type algorithm and CPLEX discretization. Note: if you have no CPLEX you should comment all starting from line 79 to the end of the file
    python MCQN_test.py
  4. For the explanations on parameters and results look to the comments in the code and to the results.md