Name
Title | ||
|---|---|---|
Incorporating domain-specific heuristics in a particle swarm optimization approach to the quadratic assignment problem. |
Abstract | ||
|---|---|---|
We propose two variations on particle swarm optimization (PSO): the use of a heuristic function as an additional biasing term in PSO solution construction; and the use of a local search step in the PSO algorithm. We apply these variations to the hierarchical PSO model and evaluate them on the quadratic assignment problem (QAP). We compare the performance of our method to diversified-restart robust tabu search (DivTS), one of the leading approaches at present for the QAP. Our experimental results, using instances from the QAPLIB instance library, indicate that our approach performs competitively with DivTS. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s12293-014-0141-y | Memetic Computing |
Keywords | Field | DocType |
Swarm intelligence,Hierarchical particle swarm optimization,PSO,Quadratic assignment problem,Robust tabu search,Statistical significance | Particle swarm optimization,Mathematical optimization,Quadratic assignment problem,Swarm intelligence,Multi-swarm optimization,Heuristics,Artificial intelligence,Local search (optimization),Machine learning,Mathematics,Tabu search,Metaheuristic | Journal |
Volume | Issue | ISSN |
6 | 4 | 1865-9284 |
Citations | PageRank | References |
5 | 0.44 | 44 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ayah M. Helal | 1 | 8 | 2.86 |
| Ashraf M. Abdelbar | 2 | 243 | 25.43 |