Added manual

A detailed manual has been added to assist users with getting their problems input into the code and understanding all of the options/settings that are available.

Dual Problem and Algorithm Additions

New user input options allow the dual problem to be explicitly solved over the primal one without need for reformulation. Additionally, the Dual Simplex method has been added as an algorithm option; however, it is still in development and cannot currently initialize all problem types.

New download instructions have been added to the 'README.md' file due to a new simplified code structure.

Efficient Primal Simplex Method

This release incorporates efficiencies to the original algorithm. Time to run a more complex problem was reduced from 10 min to 40 sec. This problem was used by permission from its original authors: Mohammad Fathollahzadeh and Karl Heine. The problem was originally developed at Colorado School of Mines and was officially presented at the 2019 ASHRAE Winter Conference in Atlanta, GA.

Main efficiency additions involve sparse matrices and steep pricing schemes. An update was also made to the Phase I algorithm that searches for existing identity matrix columns. Using a double-nested for loop was too time consuming for much larger problems.

Original release of Primal Simplex Method

This is the first release that allows others to use the Primal Simplex Method code that was created using Python. Providing the use of this code expands the ability for others to solve linear optimization problems without the need for licensing other software.