24-01-2012, 03:51 PM
Ant colony optimization algorithms
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Detailed
3. Ants take the shortest route, long portions of other ways lose their trail pheromones.
In a series of experiments on a colony of ants with a choice between two unequal length paths leading to a source of food, biologists
have observed that ants tended to use the shortest route.
A model explaining this behaviour is as follows:
1. An ant (called "blitz") runs more or less at random around the colony;
2. If it discovers a food source, it returns more or less directly to the nest, leaving in its path a trail of pheromone;
3. These pheromones are attractive, nearby ants will be inclined to follow, more or less directly, the track;
4. Returning to the colony, these ants will strengthen the route;
5. If there are two routes to reach the same food source then, in a given amount of time, the shorter one will be traveled by
more ants than the long route;
Common extensions [edit]
Here are some of most popular variations of ACO Algorithms
Elitist ant system [edit]
The global best solution deposits pheromone on every iteration along with all the other ants.
Max-Min ant system (MMAS) [edit]
Added Maximum and Minimum pheromone amounts [τmax,τmin] Only global best or iteration best tour deposited pheromone. All
edges are initialized to τmax and reinitialized to τmax when nearing stagnation.
[5]
Ant Colony System
It has been presented above.
Ant_colony_optimization_algorithms.htm (5 of 25)
Ant colony optimization algorithms - Wikipedia, the free encyclopedia
Rank-based ant system (ASrank)
All solutions are ranked according to their length. The amount of pheromone deposited is then weighted for each solution, such that
solutions with shorter paths deposit more pheromone than the solutions with longer paths.
Continuous orthogonal ant colony (COAC)
The pheromone deposit mechanism of COAC is to enable ants to search for solutions collaboratively and effectively. By using an
orthogonal design method, ants in the feasible domain can explore their chosen regions rapidly and efficiently, with enhanced global
search capability and accuracy.
The orthogonal design method and the adaptive radius adjustment method can also be extended to other optimization algorithms for
delivering wider advantages in solving practical problems.
