Abstract
This chapter is aimed at giving a classification and an analysis of various hybrid optimisers based on swarm intelligence optimisation algorithms (SIOAs) by the systematic taxonomy we proposed in a recent work. The taxonomy comprises five factors including the relationship between parent optimisers, hybridisation level, operation order, type of information transfer and type of transferred information. Based on the taxonomy, a unifying framework for SIOA-based optimisers is established. Some typical SIOA-based hybrids which are divided into two parts according to the combination patterns about global search and local search are analysed in accordance with the taxonomy. By the classification-based analysis, designers can gain an insight into various possibilities for hybrid design of SIOA-based optimisers.
| Original language | English |
|---|---|
| Title of host publication | Swarm Intelligence - Volume 1 |
| Subtitle of host publication | Principles, current algorithms and methods |
| Publisher | Institution of Engineering and Technology |
| Pages | 55-83 |
| Number of pages | 29 |
| ISBN (Electronic) | 9781785616273 |
| DOIs | |
| Publication status | Published - 1 Jan 2018 |
Keywords
- Classification-based analysis
- Combinatorial mathematics
- Combinatorial mathematics
- Combinatorial mathematics
- Global search
- Hybrid design
- Hybrid optimisers
- Hybridisation level
- Information transfer type
- Local search
- Optimisation
- Optimisation
- Optimisation techniques
- Optimisation techniques
- Parent optimisers
- SIOA-based hybrids
- SIOA-based optimisers
- Search problems
- Swarm intelligence
- Swarm intelligence optimisation algorithms
- Swarm intelligence-based hybrid algorithms