In a previous post I demonstrated how to use crispLP to solve a simple linear optimization problem with well-defined objective function and constraints. I have also demonstrated how to solve a fuzzy linear optimization problem with uncertain constraints, i.e. fuzzy constraint […]

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

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

## Comparing different German transport sectors by volume, using OECD data in R

Based on my recent OECD-package related post (http://www.supplychaindataanalytics.com/oecd-package-interface-in-r-reading-german-freight-transport-data-from-oecd-directly-in-r/) I extend my recenet analysis of German transport volume development by comparing different inland freight categories in a ggplot-chart. The data, again, i querried using the OECD-package in R. From the previous […]

## Applying fredr package in R: Analyzing FRED domestic car production data for USA

## K-Means clustering performed on OECD data in R

## OECD GDP data analysis in R

## OECD package (interface) in R: Reading (German) freight transport data from OECD directly in R

## Gradient descent in R, for non-linear optimization (nloptr package)

For solving transport problems or network modelling problems, linear programming will suffice. Nevertheless, depending on the topic at hand, non-linear programming might become relevant when considering additional constraints or objectives that are non-linear. R provides a package for solving non-linear […]

## Quadratic optimization in R with quadprog: A working example

After having demonstrated linear programming in R I want to introduce quadprog, a package for modelling and solving quadratic problems. A good theoretical introduction to quadratic programming (hence “quadratic optimization”) can be found here: https://optimization.mccormick.northwestern.edu/index.php/Quadratic_programming On stackoverflow, a useful discussion […]