| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1513677 | Energy Procedia | 2012 | 7 Pages |
Abstract
In this paper, we present an improved ant colony optimization (ACO) and we use it to solve the generalized traveling salesman problem (GTSP). We design a novel optimized implementation approach to reduce the processing costs involved with routing of ants in the conventional ACO, and we also improved the performance of the ACO by using individual variation strategy. Simulation results show the speed and convergence of the ACO can be enhanced greatly, and we also get the best results in some instance of GTSP.
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