基于遗传算法的鱼骨布局多目标路径规划  

Multi-objective path planning for fishbone layout based on genetic algorithm

作　　者：易光涛 刘建胜[1] YI Guangtao;LIU Jiansheng(School of Advanced Manufacturing,Nanchang University,Nanchang 330031,China)

机构地区：[1]南昌大学先进制造学院,江西南昌330031

出　　处：《南昌大学学报（工科版）》2024年第2期239-246,共8页Journal of Nanchang University(Engineering & Technology)

基　　金：国家自然科学基金资助项目(51565036)。

摘　　要：针对鱼骨布局多目标路径规划问题,建立了以多车协同拣货总移动距离最短和负载不平衡最小的两目标路径规划模型;通过距离检测的方法在帕累托前沿面上寻找knee点,并将该knee点作为偏好信息带入r支配中,引导算法快速搜索到偏好区域,形成更好的帕累托解集,提出一种基于knee点的r支配多目标遗传算法;引入自适应交叉和变异算子,依次提高算法全局搜索能力,加速种群收敛速度,同时防止陷入局部最优,基于标准测试函数测试算法的性能,最后通过实验数据验证了该算法在鱼骨型仓库布局拣选路径优化问题上的有效性。Aiming at the multi-objective path planning problem of fishbone layout,a two-objective path planning model with the shortest total moving distance and the smallest load unbalance with multi-vehicle cooperative picking was established;The knee point on the Pareto Front was found by the method of distance detection,and the knee point was brought into the r-dominance as the preference information,the algorithm was guided to quickly search for the preference area and a better Pareto set was formed,a r-dominance genetic algorithm based on knee point was proposed;The adaptive crossover and mutation operators were introduced to sequentially improve the global search ability of the algorithm,accelerate the population convergence speed,and prevent falling into local optimum,the performance of the algorithm was tested based on the standard test function,finally,the effectiveness of the algorithm in the optimization problem of fishbone warehouse layout and picking path was verified by experimental data.

关 键 词：鱼骨型布局 多目标路径优化 负载平衡 遗传算法 

分 类 号：TH181[机械工程—机械制造及自动化] TB491[一般工业技术]