yet another source of inspiration…
When developing software prototypes to optimize linear problems, it is sometimes desirable to provide the customer with an app to avoid the need for them to install a full python environment with all dependencies. In python, there is a tool called PyInstaller for this purpose. However, there are a few hurdles that need to be… Read more Generate EXEs solving MILPs using PyInstaller in Python
In today’s blog post, let’s dive into the fascinating realm of solving Sudoku puzzles using Mixed Integer Linear Programming (MILP). Check this previous post to see how a sudoku solver can be developed in python using dynamic programming and backtracking. Sudoku, a classic logic-based number placement puzzle, has long captivated minds around the globe with… Read more How to Develop a Sudoku Solver Using Mixed Integer Linear Programming
I owe this task to Ruedi, a regular tennis player. The Tennis Court Problem (TCP) is about the following task. At the beginning of outdoor tennis, the court lines must always be cleaned first. The sweeping set is often placed in one of two typical locations, usually either on one side of the net or… Read more The Tennis Court Problem (TCP)
In this post we want to try to provide a solution to solve the Traveling Salesman Problem (TSP) using linear programming. The post is based on this excellent video from Mr. Michel Bierlaire at the EPFL. A good written documentation of the Miller Tucker Zemlin Constraint can be found here. What is a TSP? The… Read more TSP Miller-Tucker-Zemlin Subtour Elimination Constraint
Here I’ll show you a way, how to do Tabu Search with Steepest Descent with best improvement in R. Tabu Search is a local improvement heuristic used to improve existing solutions. Such heuristics are also called local search heuristics. How does Local Search work? Local search can be described in words as follows: Take initial… Read more Tabu Search in R