4. Ant Colony Optimization
Procedure ACO
Begin
initialize the pheromone
while stopping criterion not satisfied do
position each ant on a starting node
repeat
for each ant do
chose next node
end for
until every ant has build a solution
update the pheromone
end while
end
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7. ACO for Workforce Planning
Graph of the Problem
• The node (i,j,z) corresponds to worker i to be
assigned to the job j for time z.
• Every ant starts to create their solution from
random node
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8. ACO for Workforce Planning
Transition Probability
lzcz ijijijijl /
otherwise
tallowedjif
t
k
tallowedb iblib
ijlij
k
ijl k
0
)(
)(obPr )(
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9. ACO for Workforce Planning
Solution Construction
• Feasible solution is constructed F=cost to
perform assigned tasks
• The solution is not feasible F=-1
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10. Algorithm Parameters
• Number of ants – 20
• Number of iterations – 100
• Evaporation coefficient – 0.5
• Set of workers – 20
• Set of jobs – 20
• Max assigned workers - 10
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