差分变异和交叉迁移的生物地理学优化算法

Biogeography-based Optimization Algorithm with Differential Mutation and Cross Migration

为了增强生物地理学优化(BBO)算法的优化性能,提出了一种差分变异和交叉迁移的BBO算法(DCBBO).首先用差分扰动操作替换BBO算法的变异操作,形成差分变异算子,强化了探索能力;其次用基于维度的垂直交叉操作取代BBO算法的迁移操作,形成交叉迁移算子,提升开采能力的同时又注重了探索能力;最后,为平衡算法的探索和开采,将启发式水平交叉操作融入交叉迁移算子中,形成混合交叉迁移算子,进一步提升开采能力.在不同维度的一组常用基准函数上进行了大量实验,结果表明,与其他state-of-the-art算法相比,DCBBO优化能力显著,稳定性更强,运行速度更快.

In order to enhance the optimization performance of the biogeography-based optimization(BBO)algorithm,an improved BBO algorithm with differential mutation and cross migration(DCBBO)was proposed.Firstly,BBO′s mutation operation was replaced by a differential disturbance operation to form a differential mutation operator.It could improve the exploration.Secondly,a dimension-based vertical crossover operation was used instead of BBO′s original migration operation to generate a cross migration operator.It could improve the exploitation and emphasize the exploration.Finally,to balance the exploration and exploitation,a heuristic horizontal crossover operation was merged into the cross operator to obtain a hybrid cross migration operator.It could further improve the exploitation.A large number of experiments were made on a set of common benchmark functions with different dimensions.The results showed that DCBBO could obtain more significant optimization ability,stronger stability and faster running speed compared with other state-of-the-art algorithms.