In a several other posts on Google’s ortools module in Python I have already solved the linear optimization problem stated below. The problem is a continuous problem as all optimization variables are from a continuous solution space. I could think […]

## Lean coding of simple linear optimization ortools models in Python

## Simple linear programming with Google ortools in Python

## Multi-objective linear optimization with weighted sub-problems, using PuLP in Python

## Multi-objective linear optimization with PuLP in Python

## Continuous linear optimization in PuLP (Python)

## Solving linear problem with fuzzy constraints by sampling beta with FuzzyLP in R

## Linear optimization with fuzzy constraints conducted in R with FuzzyLP

## Simple linear problem with FuzzyLP, using crispLP and basic simplex

## Linear optimization in Python: Using SciPy for linear programming

## Cost minimal production scheduling – solving the assignment problem with lpSolve in R

## Solving linear transport problem with lp.transport in R, using lpSolve

## Simple linear programming with integer variables in R, using lpSolve

In the previous post (https://www.supplychaindataanalytics.com/solving-a-simple-linear-programming-problem-using-lpsolve-in-r/) I demonstrated how a simple linear optimization problem can be modelled and solved using the lpSolve package in R. In this post I want to add the topic of modelling integer variables. In the previous […]