Name
Abstract | ||
|---|---|---|
In this work, the parallelization of some Multi-Objective Ant Colony Optimization (MOACO) algorithms has been performed. The aim is to get a better performance, not only in running time (usually the main objective when a distributed approach is implemented), but also improving the spread of solutions over the Pareto front (the ideal set of solutions). In order to do this, colony-level (coarse- grained) implementations have been tested for solving the Bicriteria TSP problem, yielding better sets of solutions, in the sense explained above, than a sequential approach. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21498-1_40 | IWANN (2) |
Keywords | Field | DocType |
pareto front,bicriteria tsp,sequential approach,parallel approach,ideal set,multi-objective ant colony optimization,better set,better performance,main objective,bicriteria tsp problem | Ant colony optimization algorithms,Mathematical optimization,Computer science,Multi-objective optimization,Implementation,Travelling salesman problem | Conference |
Volume | ISSN | Citations |
6692 | 0302-9743 | 4 |
PageRank | References | Authors |
0.42 | 5 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. M. Mora | 1 | 99 | 10.00 |
| J. J. Merelo | 2 | 363 | 33.51 |
| P. A. Castillo | 3 | 134 | 13.95 |
| M. G. Arenas | 4 | 48 | 6.27 |
| P. García-Sánchez | 5 | 27 | 3.00 |
| J. L. J. | 6 | 4 | 0.42 |
| G. Romero | 7 | 81 | 7.38 |