1. Ant Colony Optimization with Multiple Objectives
Hong Zhou
Computer Systems Lab Period 2

2. Ant Colony Optimization
Based on how real ants cooperate to find food
Useful method to find near optimal paths.
Ants choose their individual paths based on pheromones left by other ants.
They end up all going on one path, the near optimal solution

3. Multiple Objectives
Many variables effect how good a path is in real life
Could be weighted differently
Results in different near optimal solutions

4. Possible Application Military path finding Speed versus Safety
Left is the faster route, right the safer. Lighter means higher elevation, darker lower

5. Development ACO, single objective Two objectives Weighting objectives
Two pheromones
Two ‘distances’
Weighting objectives
Check against single objective

6. Expected Results Report the value of each objective
If all weight on one objective, result matches single objective path
Objective with more weight should be more optimized
Results for the military algorithm pictures shown earlier