基于遗传算法的多头组合秤称重优化  

Optimization of Weighing for Multi-Head Combination Weigher Based on Genetic Algorithm

作　　者：丁威涛 苏宇锋[1] DING Wei-tao;SU Yu-feng(School of Mechanical and Power Engineering,Zhengzhou University,He'nan Zhengzhou 450001,China)

机构地区：[1]郑州大学机械与动力工程学院,河南郑州450001

出　　处：《机械设计与制造》2022年第8期91-94,共4页Machinery Design & Manufacture

基　　金：国家重点研发计划(2018YFD0400704)。

摘　　要：首先介绍了多头组合秤的工作原理,就传统多头组合秤采用的穷举法和动态规划算法所存在的问题,提出了基于遗传算法的组合秤称重优化设计。针对组合称重时部分称重斗长时间不被选中的问题,引进优先级的概念,并对遗传算法种群在进化过程中出现违反约束的个体,提出基于“重量优先”的修复方法。仿真结果表明,此算法收敛平稳迅速,组合成功率达到98%以上,完成一次组合分析的时间小于0.15s,称重斗的最大优先级数控制在20以内。基于遗传算法的多头组合秤既能确保组合合格率也能保证物料的新鲜度,能很好的满足组合要求。We firstly introduce the working principle of the multi-head combination weighers,and propose an optimized design of weighing for combination weighers based on the genetic algorithm to solve the existing problems in the exhaustive method and the dynamic programming method adopted by the traditional combination weighers.In addition,we bring a concept of priority to solve the problem that some weighing hoppers are not selected for a long time during combination,and advance a repair strategy based on“weight first”to deal with the individuals who violate constraints in the evolution process of genetic algorithm population.The results of simulation experiments indicate that,this algorithm converges stably and quickly,with the success rate over 98%,the time completed a combined analysis less than 0.15s,and the maximum priority number of weighing hopper under 20.The multi-head combination weigher based on genetic algorithm can not only ensure the qualified rate of combination,but also keep the freshness of materials,which fulfills the combination requirements well.

关 键 词：多头组合秤 工作原理 遗传算法 优化设计 优先级 修复方法 

分 类 号：TH16[机械工程—机械制造及自动化] TH715[自动化与计算机技术—计算机系统结构] TP301.6[自动化与计算机技术—计算机科学与技术]