A unifying framework for swarm intelligence-based hybrid algorithms
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.
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