改进的NSGA-Ⅱ算法的柔性物料搬运策略  

Flexible Material Handling Strategy Based on Improved NSGA-Ⅱ Algorithm

作　　者：潘野 刘晓婷[1] 刘清涛[1] 武凯 PAN Ye;LIU Xiao-ting;LIU Qing-tao;WU Kai(Key Laboratory for Highway Construction Technology and Equipment of Ministry of Education,Chang’an University,Xi’an 710064,China)

机构地区：[1]长安大学道路施工技术与装备教育部重点实验室,西安710064

出　　处：《科学技术与工程》2021年第1期240-247,共8页Science Technology and Engineering

基　　金：国家自然科学基金(51305042);中央高校基本科研业务费高新技术项目(300102259201)。

摘　　要：针对传统的装配车间拉动式物料配送存在拣货效率低和配送成本高的问题,提出了以搬运机器人为中心的柔性物料配送策略。建立了以完工时间、延期时间、负载和能耗等目标最小化的多目标多机器人协作配送调度模型;并结合模型特点提出了一种改进的非支配排序遗传算法(non-dominated sorting genetic algorithm-II,NSGA-Ⅱ),对算法的流程、编码方法和遗传算子进行了设计和改进。最后以某汽车部件装配车间为例,运用改进的NSGA-Ⅱ算法对所建模型进行求解,并与经典的NSGA-Ⅱ算法进行了对比分析,验证了算法的可行性和有效性。结果表明,改进的NSGA-Ⅱ算法在求解柔性物料配送问题时具有更优的性能。Aiming at the problems of low item-picking efficiency and high handling-cost in the traditional pull-type material distribution in assembling workshop,a robot-orientated flexible strategy for material handling was proposed.A multi-objective and multi-robot cooperative scheduling model for distributing and dispatching was established to minimize the completion time,delay time,load and energy consumption,from which an improved non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)algorithm was proposed.The flow,coding method and genetic operator of the algorithm were designed and improved.Finally,taking an automobile-part assembling workshop as an example,the improved NSGA-Ⅱ algorithm was applied to solve the model,and the results were compared with those of the classical NSGA-Ⅱ algorithm,thus the feasibility and effectiveness of the algorithm were verified.The improved NSGA-Ⅱ algorithm show better performance in solving problems of flexible material handling.

关 键 词：搬运机器人 柔性物料配送 多目标模型 改进的NSGA-Ⅱ算法 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置]