基于全局最优和差分变异的头脑风暴优化算法

针对头脑风暴优化(brain storm optimization,BSO)算法的选择操作中仅部分个体更新追随全局最优和变异操作中步长不能自适应的问题,采用追随全局最优策略以充分利用全局最优信息,并用差分变异代替原来的高斯变异以自适应调节变异步长,提出了基于全局最优和差分变异的BSO (global-best diff...

Global-best difference-mutation brain storm optimization algorithm

To solve the problems that only some new individuals follow the global-best in the selection operation of the brain storm optimization (BSO) algorithm and mutation step without adaptation in the mutation operation, a global-best difference-mutation BSO (GDBSO) algorithm is proposed. The following global optimal strategy is applied to make full use of the global optimal information and the difference mutation is used to replace the original Gaussian mutation to adjust the mutation step adaptively. The comparison of extremum optimization of six standard test functions in Matlab simulation shows that GDBSO solves the existing problem of low search efficiency of the original BSO and greatly improves the searching precision and speed of the algorithm. The simulation of GDBSO with autonomous underwater vehicle (AUV) path planning application verifies its availability and practicability.