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.
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.
作者
张新艳
周雨晴
ZHANG Xinyan;ZHOU Yuqing(School of Mechanical Engineering,Tongji University,Shanghai 201804,China)
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2019年第11期1683-1690,共8页
Journal of Tongji University:Natural Science
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
layout of fishbone warehouse
order picking routing optimization
chaos theory
simulated annealing particle swarm optimization
