电子学报 ›› 2021, Vol. 49 ›› Issue (5): 1001-1012.DOI: 10.12263/DZXB.20200315

• 学术论文 • 上一篇    下一篇

基于改进细菌觅食算法的自动化立体仓库集成优化

董海1, 齐新娜2   

  1. 1. 沈阳大学应用技术学院, 辽宁沈阳 110000;
    2. 沈阳大学机械工程学院, 辽宁沈阳 110000
  • 收稿日期:2020-03-30 修回日期:2020-08-22 出版日期:2021-05-25 发布日期:2021-05-25
  • 作者简介:董海 男,1971年出生,山东淄博人.教授,博士,主要从事先进生产系统建模优化与控制、供应链管理等方面研究;齐新娜 女,1994年出生,辽宁阜新人.工业工程专业硕士研究生,就读于沈阳大学机械工程学院,主要从事车间调度、生产流程优化与控制等方面的研究. E-mail:1205344726@qq.com
  • 基金资助:
    国家自然科学基金(No.71672117);辽宁省重点研发计划(No.2019JH8/10100056)

Integrated Optimization of Automated Warehouse Based on Improved Bacterial Foraging Algorithm

DONG Hai1, QI Xin-na2   

  1. 1. College of Applied Technology, Shenyang University, Shenyang, Liaoning 110000, China;
    2. College of Mechanical Engineering, Shenyang University, Shenyang, Liaoning 110000, China
  • Received:2020-03-30 Revised:2020-08-22 Online:2021-05-25 Published:2021-05-25

摘要: 针对自动化立体仓库存在的出入库任务多、堆垛机利用率失衡、产品质量差别大及任务执行过程对质量产生影响的问题,提出一种基于权重策略及非均匀消除-扩散概率分布的情绪化细菌觅食算法.构建以运行时间最小化、堆垛机利用率均衡化、货架稳定性、对产品质量影响程度为目标的集成优化模型;针对细菌觅食算法存在的趋化步长不确定及消除-扩散概率恒定等不足,在趋化过程中引入高斯分布搜索机制更新个体位置,避免算法陷入局部最优;引入情绪化突变,并在突变过程引入权重策略更新个体速度,并赋予细菌个体情绪感知因子实现个体速度自适应更新;针对原始算法消除-扩散概率的恒定性,提出非均匀概率分布代替传统的常数分布,以确保种群多样性.仿真及算法对比结果表明,本文提出的算法具有较好的性能.

关键词: 自动化立体仓库, 细菌觅食算法, 情绪化突变, 高斯分布搜索机制, 权重策略, 非均匀概率分布

Abstract: In view of the problems existing in the automated warehouse,such as many in and out tasks,unbalanced utilization of stacker,great difference in product quality and the impact of task execution process on quality,an emotional bacteria foraging algorithm based on weight strategy and non-uniform elimination diffusion probability distribution is proposed.In order to minimize the running time,equalize the utilization rate of stacker,stabilize the shelf and influence the quality of products,an integrated optimization model is built.In view of the shortcomings of the bacterial foraging algorithm,such as uncertain chemotaxis step length and constant elimination diffusion probability,the Gaussian distribution search mechanism is introduced to update the individual position in the chemotaxis process to avoid the algorithm falling into local optimization,and the emotion is introduced in the mutation process,the weight strategy is introduced to update the individual speed,and the individual emotion perception factor is given to realize the adaptive step size to avoid the premature convergence of the algorithm; around the constancy of probability in the elimination diffusion process,the non-uniform probability distribution is proposed to replace the traditional constant distribution to ensure the population diversity.Simulation and algorithm comparison results show that the proposed algorithm has better performance.

Key words: automated warehouse, bacterial foraging algorithm, emotional mutation, Gaussian distribution search mechanism, weight strategy, non-uniform probability distribution

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