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基于鱼骨型仓库的拣选路径问题优化
引用本文:张新艳,周雨晴.基于鱼骨型仓库的拣选路径问题优化[J].同济大学学报(自然科学版),2019,47(11):1683.
作者姓名:张新艳  周雨晴
作者单位:同济大学 机械与能源工程学院, 上海 201804,同济大学 机械与能源工程学院, 上海 201804
摘    要:为提高鱼骨型仓库布局下的订单拣选效率,基于拣货路径距离计算模型和以最小化拣货路径总距离为优化目标的拣选路径优化模型,提出一种混沌模拟退火粒子群优化算法,引入混沌理论使粒子更高效地遍历搜寻空间,同时结合了模拟退火算法的概率突跳特点使算法在迭代后期仍具有较好的全局寻优能力.最后,通过实例仿真验证了该算法在解决鱼骨型仓库布局拣选路径优化问题上的有效性,并通过与其他算法比较,证明了该算法的先进性,为鱼骨型仓库布局下拣选路径规划问题提供了新的解决思路.

关 键 词:鱼骨型仓库布局  拣货路径优化  混沌理论  模拟退火粒子群优化算法
收稿时间:2019/1/25 0:00:00
修稿时间:2019/8/14 0:00:00

Order Picking Routing Optimization on Fishbone Aisle Warehouse
ZHANG Xinyan and ZHOU Yuqing.Order Picking Routing Optimization on Fishbone Aisle Warehouse[J].Journal of Tongji University(Natural Science),2019,47(11):1683.
Authors:ZHANG Xinyan and ZHOU Yuqing
Institution:School of Mechanical Engineering, Tongji University, Shanghai 201804, China and School of Mechanical Engineering, Tongji University, Shanghai 201804, China
Abstract:To improve the order picking efficiency in the fishbone aisle warehouse, a chaotic SAPSO (Simulated annealing particle swarm optimization algorithm) was proposed based on the picking path distance calculation model and the picking path optimization model with the minimum distance of the picking path as the optimization objective. The chaos theory was introduced to improve the global convergence property. The SA (simulated anneaing algorithm) was adopted to make the algorithm able to jump out of the local optimization and achieve global optimization. Finally, the outperformance of chaotic SAPSO algorithm to solve order picking optimization on fishbone aisle warehouse was verified by the simulation results and the comparison with other algorithms, and it provides a new solution to order picking problem in fishbone aisle warehouses.
Keywords:layout of fishbone warehouse  order picking routing optimization  chaos theory  simulated annealing particle swarm optimization
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