Nature inspired optimization algorithms / Algorithm-based Staffing with Ant Colony Optimization

Optimization algorithms can be used to solve complex optimization problems. These are problems where there are too many options to calculate the score for each solution. For instance, this is the case if we try to automatically staff projects and the team score ought to reflect interdependencies between team members.
Genetic algorithms and ant colony optimization are very intuitive optimization algorithms that are inspired by nature. Genetic algorithms are based on natural selection, and the ant colony optimization is based on the behavior of ants: they communicate using pheromone to find the shortest path to food sources.
In this talk, I will provide a gentle introduction to genetic algorithms and ant colony optimization with a focus on the application of the ant colony optimization algorithm to solve an algorithm-based staffing task.