Name
Abstract | ||
|---|---|---|
We present two enhancements to the local search strategy for Incremental Ant Colony Algorithm (IACOR), that uses Multi-Trajectory Local Search (Mtsls1) as the exploitation engine. First, a new method to handle bound constraints and a modified architecture for Mtsls1 is proposed. The second approach involves a parallel architecture for Mtsls1 along each dimension of the function. We evaluate our approaches on the Soft Computing (SOCO) benchmark functions. The reference approach takes 16% more function evaluations on an average. The proposed parallel approach provides a reduction in the run-time. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2739482.2764661 | GECCO (Companion) |
Field | DocType | Citations |
Ant colony optimization algorithms,Architecture,Mathematical optimization,Global optimization,Computer science,Artificial intelligence,Soft computing,Local search (optimization),Machine learning,Parallel architecture | Conference | 1 |
PageRank | References | Authors |
0.35 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Udit Kumar | 1 | 1 | 1.36 |
| jayadeva | 2 | 67 | 10.50 |
| sumit soman | 3 | 20 | 7.53 |