基于微细菌群体趋药性的函数优化算法

Function Optimization Method Based on Micro-Bacterial Colony Chemotaxis Algorithm

在细菌群体趋药性(bacterial colony chemotaxis,BCC)优化算法的基础上,借鉴微遗传算法的思想,提出了一种新的优化算法——微细菌群体趋药性(micro bacterial colo-ny chemotaxis,M-BCC)算法。M-BCC算法利用两个菌群(寻优菌群和库存菌群)来寻优,寻优菌群使用BCC算法来寻找最优解,库存菌群保证了寻优菌群的多样性。对Ras-trigin函数和Schaffer's f6函数优化仿真,结果表明,微细菌群体趋药性算法的成功率分别达到了95%和52%,与遗传算法和BCC算法相比,优化效果较好。

This paper proposes a new optimized algorithm that is the Micro-BCC algorithm based on the Bacterial Colony Chemotaxis optimized algorithm. M-BCC algorithm makes use of two bacterial colonies （optimizing bacterial colony and storage bacterial colony） to find the optimum. Optimizing bacterial colony is to find the optimum by BCC algorithm and storage bacterial colony is to ensure the variety of optimizing bacterial colony. The simulation of Rastrigin function and Schaffer＇s f6 function optimization using M-BCC algorithm shows success rate of M-BCC can achieve 95% and 52% separately, and the algorithm is a good optimization algorithm comparing with genetic algorithm and BCC algorithm.