Abstract: To solve the premature convergence problem of harmony search (HS) algorithm, this paper proposes a new harmony search algorithm based on shuffled frog leaping and bacterial foraging (SFLBF-HSA). This paper also introduces the ideas to improve search mechanism of harmony tones based on HS algorithm, such as the global search in shuffled frog leaping algorithm (SFLA), the attraction and exclusion signal in bacterial foraging optimization algorithm (BFOA). Firstly, by proposing harmony tones study strategy, namely attraction signal, the worst harmony individual is made searching in the positive direction to keep towards the global optimum individual. Secondly, by proposing harmony tones adjustment strategy, namely exclusion signal, the worst harmony individual is made searching in the opposite direction to keep away from the local optimum individual and search in the direction of other optimal individuals. In the two searching strategies, the non-linear dynamic characteristic of global sharing factor is simultaneously used to restrain randomly searching. The results of benchmark function comparison experiments show that SFLBF-HSA can effectively improve the convergence speed and precision in optimization problems of unimodal and multimodal functions. Applying SFLBF-HSA in image segmentation of crop seeds, the results show that this algorithm can improve segmentation effect. Especially for images of biggish and approximate circle seeds, the detection rates and successful recognition rates are effectively improved. 

Key words: harmony search algorithm, shuffled frog leaping, bacterial foraging, global sharing factor, function optimization, optimization performance, image segmentation

摘要： 针对和声搜索算法存在早熟、收敛停滞等问题，提出了一种基于混合蛙跳细菌觅食的和声搜索算法（harmony search algorithm based on shuffled frog leaping and bacterial foraging，SFLBF-HSA）。引入混合蛙跳算法全局搜索及细菌觅食优化算法群聚吸引、排斥信号等思想，对和声音调搜索机制进行了改进。首先，提出和声音调学习策略（即吸引信号），利用全局最优和声个体对最差和声个体进行正方向的差异扰动，保持搜索朝向最优个体；其次，提出和声音调调节策略（即排斥信号），利用全局最优和声个体对最差和声个体进行反方向的差异扰动，保持搜索远离局部最优个体并朝向其他优秀个体。在两种策略搜索中，同时利用全局共享因子的非线性动态特点抑制搜索的随机性。Benchmark函数对比实验结果表明，改进后算法在单峰值和多峰值函数寻优问题上收敛速度和精度均有显著提高。将SFLBF-HSA应用于作物籽粒图像分割，提高了分割效果，对颗粒较大，似圆形状作物籽粒图像分割后，识出率和识别成功率有显著提高。

关键词: 和声搜索算法, 混合蛙跳, 细菌觅食, 全局共享因子, 函数寻优, 优化性能, 图像分割