Combining two pheromone structures for solving the car sequencing problem with Ant Colony Optimization
The car sequencing problem involves scheduling cars along an assembly line while satisfying capacity constraints. In this paper, we describe an Ant Colony Optimization (ACO) algorithm for solving this problem, and we introduce two different pheromone structures for this algorithm: the first pheromone structure aims at learning for good sequences of cars, whereas the second pheromone structure aims at learning for critical cars. We experimentally compare these two pheromone structures, that have complementary performances, and show that their combination allows ants to solve very quickly most instances.
car sequencing problem ant colony optimization multiple pheromone structures