Resumen
The article reveals that even with ever-increasing computing power as of August 1, 2002, there are still many types of problems that are very difficult to solve. Particularly, combinatorial optimization problems continue to pose challenges to scientists. An example of this type of problem can be found in product design. Genetic algorithms use biological methods such as reproduction, crossover and mutation to quickly search for solutions to complex problems. More recently, scientists have been turning to insects for ideas that can be used for heuristics. In this context, it is asserted that following a trail of insects as they work together to accomplish a task offers unique possibilities for problem solving. Many aspects of the collective activities of social insects such as ants are self-organizing meaning that complex group behavior emerges from interactions of individuals who exhibit simple behaviors by themselves. Ant colony optimization is a meta-heuristic that uses artificial ants to find good solutions to difficult combinatorial optimization problems.