Chapter 2:
Ant Foraging Behavior, Combinatorial Optimization, and Routing in
Communications Networks
Josh White, J. Chase Crafton
Chapter 2:
Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks
„
Natural optimization
„
The Binary Bridge experiment
Ai : The number of ants that have used
branch A after i ants have used the bridge.
PA: Probability an ant will choose to go down
path A.
n: The degree of non-linearity of the choice
function.
k: The degree of attraction of an unmarked
branch.
Chapter 2:
Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks
„
Pheromone evaporation
„
Pheromone evaporation allows ants to
adapt to changing environments
„
Allows ants to avoid being trapped in a
suboptimal solution.
Chapter 2:
Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks
Chapter 2:
Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks
„
Ants solve the minimal Spanning tree
problem
Chapter 2:
Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks
„
The raid patterns of army ants