首页|基于GP-PS的分布式加工与装配多级车间调度规则自动设计方法

基于GP-PS的分布式加工与装配多级车间调度规则自动设计方法

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分布式加工与装配多级制造系统由多个用于加工零件的作业车间和用于装配产品的一般流水车间组成.动态到达的订单涉及多层产品结构,零件需齐备之后才可装配.该类多级车间的管控涉及订单分配、加工和装配任务调度联合决策问题,其关键在于实现两级生产的精准化协同目的.针对分布式加工与装配多级车间调度问题,提出了一种基于GP-PS的分布式加工与装配多级车间调度规则自动设计方法.首先,以最小化订单拖期率为目标,建立了订单分配、加工和装配任务调度联合决策的数学模型;然后,提出了一种改进型遗传规划算法,用以集成进化多级调度规则,设计了一类种群优化机制来避免算法陷入局部收敛,同时嵌入了并行仿真技术,有效减少了训练时间;最后,进行了仿真实验,对改进型遗传算法的性能进行了验证.研究结果表明:人工规则组、标准遗传规划算法及改进型遗传算法得到的订单拖期率分别为6.44%、5.65%、2.67%.基于并行仿真优化的改进型GP算法较数十个优选的人工规则组及标准GP算法生成的最优规则组,能取得更明显的综合性能优势.使用该算法针对DPAMW调度问题自动设计一体化调度的多级规则是可行的、有效的.
Method of automatic design of scheduling rules for distributed processing and assembly multistage workshop based on GP-PS
Distributed processing and assembly multistage manufacturing system consist of multiple job shop for processing parts and a general assembly flow shop for partial and final assembly.Dynamic orders with multi-layer product structures require part matching before assembly.The control of such multistage shop involves joint decision-making on order allocation,processing,and assembly jobs scheduling for precise coordination between the two levels of production.An automatic design method of scheduling rules for distributed machining and assembly multistage workshops based on genetic programming based on parallel simulation(GP-PS)was proposed.Firstly,a mathematical model was established to minimize the percentage of tardy product.Then,an improved genetic programming algorithm was introduced to integrate evolutionary multistage scheduling rules.A population optimization mechanism was designed to prevent the algorithm from converging locally,while parallel simulation technology was embedded to effectively reduce training time.Finally,simulation experiments were conducted to validate the performance of the improved genetic algorithm.The experimental results show that the percentage of tardy product obtained from the manual rule set,standard genetic programming,and improved algorithm is respectively 6.44%,5.65%and 2.67%.The improved GP algorithm based on parallel simulation optimization can achieve more obvious comprehensive performance advantages than dozens of preferred artificial rule groups and the optimal rule groups generated by standard GP algorithm.It is feasible and effective to use this algorithm to automatically design multi-level rules of integrated scheduling for DPAMW scheduling problem.

multistage manufacturing systemdistributed manufacturing systemdistributed processing and assembly multistage workshop(DPAMW)genetic programming based on parallel simulation(GP-PS)scheduling rulegenetic programmingsimulation optimization

邹杰、刘建军、曾创锋

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广东工业大学 广东省计算机集成制造重点实验室,广东 广州 510006

多级制造系统 分布式制造系统 分布式加工与装配多级车间 并行仿真优化的遗传规划算法 调度规则 遗传规划 仿真优化

国家自然科学基金资助项目国家自然科学基金资助项目

5237548951975129

2024

10.3969/j.issn.1001-4551.2024.09.011

机电工程
浙江大学　浙江省机电集团有限公司

机电工程

CSTPCD北大核心
影响因子：0.785
ISSN：1001-4551
年,卷(期)：2024.41(9)
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