基于情绪化细菌觅食算法的货位分配优化

Optimization of Location Allocation Based on Emotional Bacteria Foraging Algorithm

文章针对自动化立体仓库货位分配优化问题,提出一种基于非均匀消除-扩散概率的情绪化细菌觅食算法。构建以堆垛机于一个生产周期内兼顾平均运行时间和出入库任务对产品质量影响程度的多目标优化模型;针对传统细菌觅食算法在优化过程中存在的趋化步长不确定及消除-扩散概率恒定等不足,在趋化步骤中利用古斯分布搜索机制对细菌个体位置进行更新,以解决搜索能力差及易陷入局部最优的问题,引入情绪感知因子,利用情绪智能的突变实现自适应趋化步长,避免过早收敛;围绕细菌个体在消除-扩散过程中概率的恒定性问题,提出利用线性和非线性概率分布代替传统的常数分布实现非均匀分布,同时引入动力因子随机值,降低算法计算成本;仿真测试及算法对比结果表明,文章提出的算法较传统的细菌觅食算法及遗传算法在解决该类问题上具有较好的收敛性,且可保证种群于优化过程中的多样性。

In this paper,an emotional bacteria foraging algorithm based on the probability of non-uniform elimination diffusion is proposed to optimize the location allocation of automated warehouse.A multi-objective optimization model is constructed,in which the average running time of stackers and the impact of the in and out tasks on the product quality are considered in one production cycle.Aiming at the shortcomings of traditional bacterial foraging algorithm,such as uncertain chemotaxis step length and constant elimination diffusion probability,the guss distribution search mechanism is used to update the bacterial individual position in the chemotaxis step to solve the problem For the problems of poor search ability and easy to fall into local optimum,the emotional perception factor is introduced,and the mutation of emotional intelligence is used to realize the adaptive chemotaxis step length,so as to avoid premature convergence.Around the problem of probability constancy of bacteria in the process of elimination diffusion,the linear and non-linear probability distribution are proposed to replace the traditional constant distribution,so as to realize the non-uniform distribution,and the dynamic factor is introduced The results of simulation test and algorithm comparison show that the algorithm proposed in this paper has better convergence than the traditional bacterial foraging algorithm and genetic algorithm in solving this kind of problems,and can ensure the diversity of population in the optimization process.