1. Multiple Ant Colonies Presented by Brandon Borkholder
Based on MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Windows

2. Problem Route a fleet of delivery vehicles Minimize cost and time
Primary variable is cost/tours
Most realistic as vehicles are variable cost

3. Solution
Define two Ant Colony Systems (ACS)
One for each parameter

4. Solution, cont. Cooperate by pheromone updating
Pheromone levels indicate how desirable an arc is
Opposing influences: exploration and exploitation
Ants decide where to go (probabilistically) based on maximal pheromone levels
As an ant passes over an arc, it decreases the pheromone

5. Implementation Procedure MACS-VRPTW() Repeat
v ← #active_vehicles(ψ gb )
Activate ACS-VEI(v - 1)
Activate ACS-TIME(v)
While ACS-VEI and ACS-TIME are active
Wait an improved solution ψ from ACS-VEI or ACS-TIME
ψ gb ← ψ
if #active_vehicles(ψ gb ) < v then
kill ACS-TIME and ACS-VEI
End While
until a stopping criterion is met

6. Implementation, cont. Find an initial solution for given cost
Improve on time until we can improve on cost
Then improve on time with that parameter of cost

7. Implementation, cont.
The ants for time might not find a complete solution
Import the other edges in a greedy best-first manner

8. Alternative Methods Exact methods Tabu and large neighborhood searches
Works well for constricted time windows
Solution space is small

9. Results

10. Advantages/Disadvantages
Very fast
< 30 minutes for ~100 nodes
All the advantages of swarm
Adaptable, etc.
Disadvantages
Is a complex system with many concepts
Really not optimizing both parameters simultaneously

11. Questions