Ant Colony Optimization
Ant Colony Optimization (ACO) algorithms are based on the natural phenomenon that ants are able to find the shortest route between their nest and a food source, despite the fact that they are almost blind. By following pheromone trails, each ant reinforces good paths and avoids bad paths until the best path is found. The ACO analogy can be applied to optimizing water systems. There are many combinations of paths an ant must choose between, just as there are many combinations of pipes sizes and other infrastructure that must be evaluated.
Every ant in the ‘colony’ builds up a solution by passing through several decision points. At each decision point are a series of options, with one selected on a probabilistic basis. The series of options selected by an ant forms a ‘path’. The values of the variables determined from the path chosen by an ant are then used to calculate the total cost of that system. A cycle is complete after all ants have stepped through the network of paths. The pheromone on the paths chosen is then updated in proportion to the quality of each solution.
