自动化立体仓库固定货架拣选路径问题研究

为提高自动化立体仓库拣选效率,以存取时间最短为目标,针对单巷道固定货架拣选作业过程,构建了解决拣选作业路径优化问题的数学模型,提出结合模拟退火算法的混合粒子群算法.该算法在求解过程中用粒子群算法初始化种群,提高了优化效率,缩短了搜索时间;在迭代过程中采用模拟退火算法,利用其概率突跳能力,以避免基本粒子群算法迭代过程中陷入局部最优和早熟收敛.通过实例验证,该算法比标准粒子群算法所用时间短、收敛速度快、迭代次数少.

Chosen Path Optiomization for Fixed Shelves in AS/RS

To improve the order picking efficiency and shorten storage time in Automatic Storage & Retrieval System (AS/RS), a mathematical model was constructed to solve the problem of picking path optimization.According to the operation character of the order picking of fixed shelf storage area in a single roadway, an hybrid particle swarm algorithm combined with simulated annealing algorithm was presented.In the solution process, particle swarm optimization (PSO) was used to initialize the swarm, so as to improve the searching performance of the algorithm and optimize the results.The method can improve the optimization efficiency and shorten the searching time.In the iterative process, the simulated annealing algorithm was used to avoid premature convergence and to prevent from getting into local optimum as in the conventional PSO due to its probabilistic jumping ability.The examples show that compared with the standard PSO, the algorithm has the merits of shorter calculation time, faster convergence and fewer times of iterations.