Journal
MEMETIC COMPUTING
Volume 6, Issue 4, Pages 241-254Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s12293-014-0141-y
Keywords
Swarm intelligence; Hierarchical particle swarm optimization; PSO; Quadratic assignment problem; Robust tabu search; Statistical significance
Funding
- Brandon University Research Committee
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available