基于全局无偏搜索策略的精英人工蜂群算法

针对精英人工蜂群算法（ABC_elite）加速收敛和早熟停滞现象的矛盾，提出一种改进算法（EABC_elite）.该算法通过在雇佣蜂阶段引入全局最优解加速收敛，同时通过普通个体平衡全局最优解过大的引导作用，因此全局最优解与普通个体的信息都能得到利用而算法仍能较好平衡.在观察蜂阶段引入普通个体避免算法早熟收敛.改进算法在加速收敛与防止早熟之间取得很好的平衡，总体上没有偏向任何方向，增强了ABC_elite的全局搜索能力.实验表明，改进算法的性能显著好于ABC_elite以及最近提出的几种较高水平的改进人工蜂群算法.

Artificial Bee Colony Algorithm with Global and Unbiased Search Strategy

To settle the contradictory between convergence speed and precocity in artificial bee colony with elite-guided equations (ABC_elite),an enhanced ABC_elite (EABC_elite) is proposed.In the employed bee phase of EABC_elite,the global best (gbest) individual is introduced to the search equation to accelerate convergence,while the ordinary individual is also introduced to the search equation to balance the gbest's great lead ability,thus the information of gbest and ordinary individuals can all be used and the balance between exploration and exploitation can still be maintained.In the onlooker bee phase of EABC_elite,the ordinary individual is also introduced into the search equation to avoid the precocity.EABC_elite can keep good balance between accelerating convergence and averting precocity.It has no bias to any search directions and the global search ability of ABC_elite is enhanced.The experimental results demonstrate that EABC_elite performs significantly better than ABC_elite and other recently-developed state-of-the-art variants of artificial bee colony algorithm.