Ant Colony Optimisation

Question 1

What is Ant Colony Optimisation?

Answer 1

Population based method
Multi-point search
Colony of ants is the population

Question 2

ACO food collection

Answer 2

Food source = good solution. shortest path = most efficient way to reach that solution

Question 3

ACO trails vs solution components

Answer 3

trails = assign values to solution components. value = desirability of including those components in the final solution

Question 4

ACO pheromone deposits vs updating trail values

Answer 4

ACO updates the values associated with solution components based on the quality of the solutions they contribute to

Question 5

What parts is ACO based on?

Answer 5

Ant based solution construction. Pheromone update, iteration

Question 6

ACO metaheuristic Algorithm

Answer 6

set parameters + intialize pherome values
while(termination criteria not met){
Construct ant solutions
Perform local search
Update pheromones
}

Question 7

AAA (Artifical Ant Algorithms)

Answer 7

init pheromone trails + parameters
while (stop criteria not met){
for each ant{
construct solution using pheromone trails and heuristic info
eval solution
update pheromone trails based on quality of solution
end for
update pheromone trails globally
end while
return best solution

Question 8

learn ACO pherome formula from slides

Question 9

What are the ACO parameters?

Answer 9

Number of Ants
Pheromone evaporation rate
Pheromone intensity
Heuristic info
Ant Decision rule
Local search strategy
termination criteria