Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Using Genetic Algorithms to Optimize ACS-TSP
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
| Hi-index | 0.00 |
Marco Dorigo et al. used Ant System (AS) to explore the Symmetric Traveling Salesman Problem and found that the use of a small number of elitist ants can improve algorithm performance. The elitist ants take advantage of global knowledge of the best tour found to date and reinforce this tour with pheromone in order to focus future searches more effectively. This paper discusses an alternative approach where only local information is used to reinforce good tours thereby enhancing the ability of the algorithm for multiprocessor or network implementation. In the model proposed, the ants are endowed with a memory of their best tour to date. The ants then reinforce this "local best tour" with pheromone during an iteration to mimic the search focusing of the elitist ants. Results are compared with Ant System.