In my most recent post on linear programming I applied PuLP for solving below linear optimization problem, using two approaches. Approach #1 was based on solving a sub-problem with one objective only first, then adding the optimal outcome of that […]

## 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

## 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 […]