• 先进计算 •

### 多交互式人工蜂群算法及其收敛性分析

1. 上海电机学院 电气学院, 上海 200240
• 收稿日期:2016-09-18 修回日期:2016-10-26 出版日期:2017-03-10 发布日期:2017-03-22
• 通讯作者: 林凯
• 作者简介:林凯(1992-),男,浙江温州人,硕士研究生,主要研究方向:风电场优化调度、群智能算法;陈国初(1971-),男,江西九江人,教授,博士,主要研究方向:复杂系统建模仿真及优化与控制、风能资源评估与预测、风电功率预测;张鑫(1991-),女,湖北枣阳人,硕士,主要研究方向:风电功率预测、群智能算法。
• 基金资助:
上海市教委科研创新项目（13YZ140）。

### Multiple interactive artificial bee colony algorithm and its convergence analysis

1. School of Electrical Engineering, Shanghai Dianji University, Shanghai 200240, China
• Received:2016-09-18 Revised:2016-10-26 Online:2017-03-10 Published:2017-03-22
• Supported by:
This work is partially supported by Research Innovation Project of Shanghai Education Department (13YZ140).

Abstract: Aiming at the shortcomings of Artificial Bee Colony (ABC) algorithm, which is not easy to jump out of the local optimal value, a Multiple Interactive Artificial Bee Colony (MIABC) algorithm was proposed. The proposed algorithm was based on the basic ABC algorithm, involved the random neighborhood search strategy and the cross-dimensional search strategy, and improved the treatment when bees exceed the limit, so the search way of the algorithm became various, the algorithm itself had stronger bound and it's hard to trap in the local optimal value. Meanwhile, the convergence analysis and performance test were carried out. The simulation result based on five kinds of classic benchmark functions and experimental results for time complexity show that comparing with the standard ABC algorithm and basic Particle Swarm Optimization (PSO), this proposed method has faster convergence speed which is increased by about 30% and 65% at 1E-2 accuracy and better search precision, besides, it has significant advantages in solving high dimensional problems.