Combined pattern search optimizationalgorithm based on arterial bee colony

In recent years, a new field of research called collective intelligence Bhynhyaby problems in dynamic environments, is growing, whichfocuses on the social behavior of insects like ants and bees on the model. Bee colony optimization algorithms are evolutionaryoptimization algorithms hands, which successfully operate in discrete optimization problems. In this dissertation, a kind of pattern search algorithms Memetics Hook Jyvz by combining artificial bee hive algorithm, is proposed for optimization. Algorithm HABC, anidea attractive to the bees in artificial bees colony and artificial bee colony successfully in the global exploration capability increases. The proposed algorithm consists of two stages, the first stage: exploration are identified by the algorithm of artificial bee hive.And then the operation is completed by a pattern search. Previous studies showed that this algorithm have better results in terms of convergence rate, solution accuracy and success rate is achieved.

Keywords:

Memetics algorithms , evolutionary optimization algorithms , bee , collective intelligence