HABC algorithm |
Set ; |
INITIALIZE. |
Randomly divide the whole population into species () each possesses sub-populations (), each possesses bees; |
Randomize ’s -dimensions food source positions ; , , . |
Each sub-population with dimensions (where is randomly chosen from a set , and ). |
WHILE (the termination conditions are not met) |
for each species , |
Initialize -dimensions complete vector = (), |
which consists of the -dimensions best solution . |
Randomly all dimension indices; |
WHILE (the termination conditions are not met) |
for each sub-population , do |
repeat |
Employed Bees’ Phase: |
For each employed bee : |
Produce a new solution by using (2) |
Evaluate the new solution |
Apply Greedy selection choosing the better solution |
end |
Calulate the probability values for the solution by using (2) |
Onlooker Bees’ Phase: |
for each employed bee |
Probabilistically choose a solution according to |
Produce a new solution by (2) |
Evaluate the new solution |
Apply Greedy selection choosing the better solution |
end |
Re-initialize solutions not improved for Limit cycles |
Memorize the best solution |
for each individual of , do |
Place best solution in the complete solution newGbest by: |
newGbest = () |
Update complete solution if it improves: |
If (f(newGbest) < f(Gbest)) |
Then |
end |
end |
end WHILE |
Selct elites form neighborhood of |
= the top M best individuals of the ring topology |
Crossover & Mutation by (4) |
Update with applying Greedy selection mechanism from |
end |
find the global best solution gbest from the whole population |
memorize the best solution of each |
Set ; |
end WHILE |