Chapter Eight: Ant colony optimization
Abstract
The focus of this chapter is on another well-known population-based metaheuristic algorithm, called ant colony optimization (ACO), which is also a popular algorithm of swarm intelligence. The search behavior of ACO is inspired by the behavior of ant colonies. Examples are given to show how ants use and share distance and pheromone information to find a good path. In addition to the pseudocode for illustrating the basic idea of ACO, the equations for calculating the transition probability are provided to show how a candidate solution is constructed by an ant. The source code and simulation results of ACO will also be presented to show how to use it to solve the traveling salesman problem. The historical ...
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