Generalized swarm intelligence algorithms with domain-specific heuristics

P. Matrenin, V. Myasnichenko, N. Sdobnyakov, D. Sokolov, S. Fidanova, L. Kirilov, R. Mikhov

Abstract


In recent years, hybrid approaches on population-based algorithms are more often applied in industrial settings. In this paper, we present the approach of a combination of universal, problem-free Swarm Intelligence (SI) algorithms with simple deterministic domain-specific heuristic algorithms. The approach focuses on improving efficiency by sharing the advantages of domain-specific heuristic and swarm algorithms. A heuristic algorithm helps take into account the specifics of the problem and effectively translate the positions of agents (particle, ant, bee) into the problem's solution. And a Swarm algorithm provides an increase in the adaptability and efficiency of the approach due to stochastic and self-organized properties. We demonstrate this approach on two non-trivial optimization tasks: scheduling problem and finding the minimum distance between 3D isomers.

Keywords


Domain-specific heuristic; Job-shop scheduling; Nanoclusters; Particle swarm optimization; Potential energy surface; Swarm intelligence

Full Text:

PDF


DOI: http://doi.org/10.11591/ijai.v10.i1.pp157-165

Refbacks

  • There are currently no refbacks.


View IJAI Stats

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.