基于改进禁忌搜索的多目标自动化仓库调度

Multi-objective automated warehousing scheduling based on improved tabu search

针对产品质量和路径的多目标自动化立体仓库调度优化问题,为平衡解的收敛性和多样性,提出一种改进的多目标禁忌搜索算法。该算法的改进在于,一方面为Pareto解空间构造可行的初始解,改造了禁忌搜索的邻域结构;另一方面采用惩罚策略,使搜索能够跳出局部最优。面向出入自动化立体仓库的产品在时间上有特定要求的工业生产过程,建立了兼顾质量和路径的多目标优化模型,并运用改进的多目标禁忌搜索算法对其实现了调度优化求解。实例仿真表明,所提算法对仓库调度优化问题在解的质量及求解效率上都取得了较好的效果。

Aiming at the automated warehousing scheduling optimization problem with product quality and routing, an improved multi-objective tabu search algorithm was proposed to balance the convergence and diversity of the solu- tions. The proposed method had two distinctive improvements： the feasible initial solution was constructed for Pare- to solution space and the neighborhood structure of tabu search was improved; by using penalty strategy, the search could escape from the local optimal. Oriented to the industrial manufacturing process which had special time require- ment for the products, a multi-objective optimization model with consideration of quality and routing was built, and the improved multi-objective tabu algorithm was used to realize scheduling optimization of this model. Simulation re- sults showed that the proposed method achieved good performance on solution quality and efficiency for the automa- ted warehousing scheduling problem.