Dorigo and Di Caro predicted this algorithm in 1999, which is one of the most popular SBAs. It is a meta-heuristic algorithm that is inspired by ants’ forestry behavior, called stigmergy. It enables indirect contact between self-organizing growing systems by moving individuals across their local environment. It depends on the collaborative actions of group of ants and their shortest path finding capability to find food sources from their nest and then by tracing out pheromone trails. After that, ants choose the pathway in which a decision is based on probability influenced by the quantity of pheromone: the stronger pheromone trace, the greater its desirability. This behavior leads to a self-mechanism which leads to the formation of pathways marked by high pheromone concentration, as ants in turn drop pheromone in the direction they follow. By modeling and simulating ant’s behavior, techniques such as brood sorting, nest building are developed. This can be built for complex combinatorial problems of optimization. This algorithm was developed in 1996 and named as ant system to solve travelling salesman problem. Ant’s colony optimization algorithm is implemented with three functional blocks: ant solutions construct, pheromone update and daemon actions.
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