| Title: | Pintea CM., Matei O., Ramadan R.A., Pavone M., Niazi M., Azar A.T. (2018) A Fuzzy Approach of Sensitivity for Multiple Colonies on Ant Colony Optimization. In: Balas V., Jain L., Balas M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 634. Springer, Cham. |
| Authors: | Not Available |
| Year: | 2018 |
| Keywords: | Not Available |
| Journal: | Advances in Intelligent Systems and Computing |
| Volume: | 634 |
| Issue: | Not Available |
| Pages: | Not Available |
| Publisher: | Springer |
| Local/International: | International |
| Paper Link: | |
| Full paper | Not Available |
| Supplementary materials | Not Available |
| Abstract: |
In order to solve combinatorial optimization problem are used mainly hybrid heuristics. Inspired from nature, both genetic and ant colony algorithms could be used in a hybrid model by using their benefits. The paper introduces a new model of Ant Colony Optimization using multiple colonies with different level of sensitivity to the ant’s pheromone. The colonies react different to the changing environment, based on their level of sensitivity and thus the exploration of the solution space is extended. Several discussion follows about the fuzziness degree of sensitivity and its influence on the solution of a complex problem. |
