摘要
为了克服蝙蝠算法(BA)易陷入局部最优,收敛速度过快等缺点,以基本蝙蝠算法为基础,提出了基于禁忌搜索的蝙蝠算法(TSBA)。TSBA算法将蝙蝠算法和禁忌搜索算法相结合,采用禁忌表以及渴望水平函数的策略,使算法具有更强的全局寻优能力,有效地避免了早熟现象。为了验证该算法的有效性,采用0-1背包问题作为测试内容。实验结果表明,基于禁忌搜索的TSBA蝙蝠算法比基本的蝙蝠算法具有更强的寻优能力和搜索速度。
In order to solve disadvantages of the bat algorithm （BA）, such as easy to fall into local optimum and convergence speed is too fast, based on the fundamental bat algorithm, the bat algorithm based on tabu search （TSBA） is put forward. TSBA combines the algorithm and tabu search algorithm. The tabu list and aspiration level function are utilized to give the algorithm as better search ability. The premature phenomenon is efficiently avoided. In order to verify the effectiveness of the algorithm, 0-1 knapsack problem is used to test. The experimental results show that TSBA has better search ability and faster search speedthan the fundamental bat algorithm.
出处
《计算机时代》
2014年第12期15-18,21,共5页
Computer Era
基金
国家自然科学基金项目"实时数据流中动态模式的发现与跟踪"(60975031)
