Name
Abstract | ||
|---|---|---|
Numerical optimization techniques are applied to a variety of engineering problems. The objective function evaluation is an important part of the numerical optimization and is usually realized as a black-box simulator. For efficient solving the numerical optimization problem, new shared-memory approach is proposed. The algorithm is based on an ACO meta-heuristics, where indirect coordination between ants drives the search procedure towards the optimal solution. Indirect coordination offers a high degree of parallelism and therefore relatively straightforward shared-memory implementation. For the communication between processors, the Intel-OpenMP library is used. It is shown that speed-up strongly depends on the simulation time. Therefore, algorithm's performance, according to simulator's time complexity, is experimentally evaluated and discussed. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IPDPS.2011.176 | IPDPS Workshops |
Keywords | Field | DocType |
numerical optimization technique,simulation time,black-box simulator,indirect coordination,numerical optimization problem,numerical optimization,shared-memory aco-based algorithm,straightforward shared-memory implementation,time complexity,aco meta-heuristics,new shared-memory approach,shared memory,optimization,computational modeling,parallel processing,ant colony optimization | Global optimization,Shared memory,Degree of parallelism,Computer science,Meta-optimization,Parallel computing,Algorithm,Multi-swarm optimization,Time complexity,Optimization problem,Metaheuristic | Conference |
ISSN | ISBN | Citations |
1530-2075 E-ISBN : 978-0-7695-4577-6 | 978-0-7695-4577-6 | 1 |
PageRank | References | Authors |
0.35 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Korošec | 1 | 153 | 17.80 |
| Jurij Šilc | 2 | 220 | 19.94 |
| Marian Vajteršic | 3 | 4 | 2.41 |
| Rade Kutil | 4 | 61 | 8.80 |