Iterated Local Search From Scratch in Python
Iterated Local Search is a stochastic global optimization algorithm.
It involves the repeated application of a local search algorithm to modified versions of a good solution found previously. In this way, it is like a clever version of the stochastic hill climbing with random restarts algorithm.
The intuition behind the algorithm is that random restarts can help to locate many local optima in a problem and that better local optima are often close to other local optima. Therefore modest perturbations to existing local optima may locate better or even best solutions to an optimization problem.
In this tutorial, you will discover how to implement the iterated local search algorithm from scratch.
After completing this tutorial, you will know: