基于多维更新的改进人工蜂群算法

An improved Artificial Bee Colony algorithm based on multi-domain updating

标准人工蜂群算法采用逐维更新的策略,存在前期收敛快、易于陷入局部最优、后期解失去多样性、收敛慢的缺点。本文在解的搜索过程中,利用多维同时更新来增强解的搜索力度,随机选取多维更新的策略在后期增加解的多样性,提出了多维更新的改进人工蜂群算法,加快算法的收敛速度。用标准测试函数对改进的人工蜂群算法做寻优测试,实验结果表明该算法加快了收敛速度,进一步优化了测试函数的最优值,具有良好的寻优效果。

Standard Artificial Bee Colony(ABC)algorithm adopts the strategy of dimensional update,and has the disadvantages of fast convergence in the early stage,easily falling into local optimum,loss of diversity of solutions in the later stage and slow convergence.With the strong ability of multi-domain updating of solution exploration,which can not only strengthen the exploration,but also enrich the variety of solution,a multi-domain updating ABC algorithm is proposed in this paper.Testing the IABC algorithm with standard testing functions,experimental results show that the algorithm can not only fasten the convergence speed,but also further optimize the optimal value of the test functions,providing a better optimization performance.