CAJ | 학술논문

对蜂群算法的性能进行全面的测试和研究，实验分析了维数和粒子数对算法的影响，侦察蜂的活动对算法的影响以及初始解的位置对算法的影响。同时受遗传算法的启发，将典型的选择机制应用到蜂群算法并对其进行改进，并比较不同选择机制下蜂群算法的性能。实验结果表明，在粒子数为40，维数为10或者30，均匀分布初始解的位置，采用确定式选择法和无放回余数选择法代替蜂群算法中轮盘赌的选择方法的条件下，蜂群算法得到整体最好的优化结果。
대봉군산법적성능진행전면적측시화연구，실험분석료유수화입자수대산법적영향，정찰봉적활동대산법적영향이급초시해적위치대산법적영향。동시수유전산법적계발，장전형적선택궤제응용도봉군산법병대기진행개진，병비교불동선택궤제하봉군산법적성능。실험결과표명，재입자수위40，유수위10혹자30，균균분포초시해적위치，채용학정식선택법화무방회여수선택법대체봉군산법중륜반도적선택방법적조건하，봉군산법득도정체최호적우화결과。
A comprehensive test and study of artificial bee colony algorithm’s performance is done. A series of experi-ments including effect of dimension and colony size, effect of scout bees and effect of initial region scaling are taken and analyzed. Meanwhile, inspired by genetic algorithm, ABC algorithm is applied with typical selection mechanisms and the performance with different selection mechanisms is compared. The experimental results show that ABC algorithm can ob-tain the global best optimum result in the condition of setting colony size be 40, dimension be 10 or 30, initial region scal-ing be symmetric distributed and the selection mechanism be deterministic sampling or remainder stochastic sampling with replacement instead of roulette wheel selection used in ABC algorithm.