摘要
自动化立体仓库堆垛机的路径优化问题对提高仓库运行效率、降低成本有重要意义。目前,对于堆垛机路径优化多使用自适应遗传算法。但现有自适应遗传算法(AGA)在进化早期易陷入局部最优,结果精度不高。文章在传统自适应遗传算法基础上,从横向、纵向两个维度出发改进当前算法,修改交叉、变异概率公式,将改进后自适应遗传算法(IAGA)与模拟退火算法(SA)结合成自适应模拟退火遗传算法(ASAGA)。使用这四种算法分别对堆垛机单巷道复合作业路径最优问题建模、求解,通过对比结果得出IAGA能够解决AGA陷入局部最优的问题,ASAGA在结果精确度和收敛速度较SA、IAGA有明显提高。
The optimization of the Stacker's route in as/RS is very important to improve the efficiency and reduce the cost of the warehouse.At present,adaptive genetic algorithm(AGA)is often used to optimize the stacker's route.However,the existing adaptive genetic algorithm(AGA)is easy to fall into local optimum in the early stage of evolution,and the result precision is not high.Based on the traditional adaptive genetic algorithm,this paper improves the current algorithm from the horizontal and vertical dimensions,and modifies the formulas of crossover and mutation probability,the improved adaptive genetic algorithm(IAGA)and simulated annealing algorithm(SA)were combined to form the adaptive simulated annealing genetic algorithm(ASAGA).The four algorithms are used to model and solve the optimal problem of compound working path in single roadway of stacker,and the results show that IAGA can solve the problem of AGA falling into local optimum,compared with SA and IAGA,the accuracy and convergence speed of ASAGA were obviously improved.
作者
杨增钢
闫明
雷蕾
YANG Zenggang;YAN Ming;LEI Lei(School of Mechanical Engineering,Shenyang University of Technology,Shenyang 110870,China)
出处
《物流科技》
2024年第1期174-176,共3页
Logistics Sci-Tech
