一类新的混流装配线排产优化模型

针对混流装配线的负荷均衡化问题,建立了最优化辅助工人数量的一类新的排产优化模型,分析了混流装配线的空间间隔约束和能力约束之间的关系,让明了空间间隔约束是满足工作站能力约束的充分条件.在此基础上给出了有辅助工人参与情况下的空间间隔约束不等式.对一些非线性约束进行了线性化处理,从而可以方便地求解模型.最后,通过仿真实例验让了该方法的可行性和有效性.     

混流装配线平衡分析与算法设计

为了设计合理可靠的混流装配线并有效地提高装配线的平衡率,分析了混流装配线的特点并设计了一种以工序对调为核心思想的新算法,该算法的逻辑结构较为简易且兼容性高,能够与现有的大部分投产排序方法相结合,对装配线做进一步平衡优化处理.具体地描述了新算法的原理和执行过程,最后将该算法应用到某厂的汽车车灯线束装配线上,结果验证了该方法的有效性和可行性.     

采用遗传算法的混流装配线平衡多目标优化

针对混流装配线操作人数已知、生产节拍待定情况下的平衡问题,研究了混流装配线第二类平衡问题的优化方法,以均衡各工作站的加权平均负荷、最小化生产节拍为优化目标,建立了求解加权平均负荷与生产节拍加权和的数学模型,并运用遗传算法对其进行求解.各优化目标数量级的统一,简化了算法求解过程,在保证解的有效性的同时提高了算法求解效率.算例分析验证了算法的有效性.     

基于禁忌粒子群算法的混流装配线排序研究

为了更好地解决开放式作业域的混流装配线排序问题,建立了以最小化超载时间与平顺化零部件消耗为优化目标的混流装配线排序问题数学模型,并提出了一种禁忌粒子群算法求解该排序问题。针对标准粒子群算法在算法后期搜索精度不足以及容易陷入局部最优不能跳出的缺陷,引入了禁忌搜索算法建立了对最优微粒的重搜索机制来提高算法跳出局部最优的能力,同时给出了禁忌算法中候选解、禁忌表长度、禁忌对象、藐视准则的设置方法,并采用了随机权重的惯性权重更新方式来平衡算法的全局和局部搜索能力,最后建立了禁忌粒子群的算法流程。通过比较禁忌粒子群算法与遗传算法的实例计算结果,验证了禁忌粒子群算法在求解开放式作业域的混流装配线排序问题中的有效性和优越性。     

Metaheuristic approaches to sequencing mixed-model fabrication/assembly systems with two objectives

This paper is concerned about the sequencing problems in pull production systems which are composed of one mixed-model assembly line and one flexible fabrication flow line with limited intermediate buffers. Two objectives are considered simultaneously: minimizing the total variation in parts consumption in the assembly line and minimizing the makespan in the fabrication line. The mathematical models are presented. Since the problem is Non-deterministic Polynomial-hard (NP-hard), a multiobjective genetic algorithm is proposed for solving the models, in which a method to generate the production sequence for the fabrication line from the production sequence for the assembly line is put forward, and Pareto ranking method and sharing function method are employed to evaluate the individuals' fitness. The feasibility and efficiency of the multiobjective genetic algorithm is shown by computational comparison with an adaptive genetic algorithm and a multiobjective simulated annealing.     

基于多目标模糊决策的混流装配线排序算法

在订单生产环境下的多品种混合装配线排序问题的基础上,建立了三种目标函数:最小化生产周期时间、最小化工作站闲置与超载时间以及最大化平均负荷率.引入了一种基于模糊决策模型的改进后的混合遗传禁忌搜索算法.在求解过程中,计算出所有个体的各个目标特征值的影响度、影响度因子以及相对隶属度,将目标特征值矩阵转化为相对隶属度矩阵,应用模糊层次分析法,计算多目标排序问题中各指标的权重值,用综合评判线性加权平均模型进行评价,构造出相对适应度函数.     

A genetic-algorithm-based optimization model for scheduling flexible assembly lines

In this paper, a scheduling problem in the flexible assembly line (FAL) is investigated. The mathematical model for this problem is presented with the objectives of minimizing the weighted sum of tardiness and earliness penalties and balancing the production flow of the FAL, which considers flexible operation assignments. A bi-level genetic algorithm is developed to solve the scheduling problem. In this algorithm, a new chromosome representation is presented to tackle the operation assignment by assigning one operation to multiple machines as well as assigning multiple operations to one machine. Furthermore, a heuristic initialization process and modified genetic operators are proposed. The proposed optimization algorithm is validated using two sets of real production data. Experimental results demonstrate that the proposed optimization model can solve the scheduling problem effectively.     

非同步混装线负荷平衡与投产排序集成优化方法

为了提高非同步混流装配线的生产效率,提出了一种负荷平衡和投产排序的集成优化方法.首先通过综合优先图,将多品种装配线平衡问题转变成单品种平衡问题;通过设计组合优先启发式方法,以最小化生产节拍为目标,生成平衡方案;在平衡方案基础上,按照生产需求,采用考虑有限缓冲区容量的NEH(Nawaz-Enscore-Ham)算法,获得...     

基于遗传算法和仿真分析的混合装配线平衡问题研究

为兼顾混合装配线平均负荷平衡和瞬时负荷平衡,提出了一种综合运用遗传算法和仿真分析的混合装配线平衡问题的求解方法.首先,基于综合作业顺序图和多品种产品在每个作业任务上的平均作业时间,采用遗传算法求解混合装配线平衡问题,其优化目标是均衡各工作站平均作业时间;然后,对遗传算法求解的一组较优解,从瞬时负荷平衡方面进行仿真分析,其优化目标是最大化各工作站利用率;最后,综合两个优化目标确定混合装配线平衡问题的最优解.通过算例分析,验证了求解方法的有效性.     

Multi-objective artificial bee colony algorithm for simultaneous sequencing and balancing of mixed model assembly line

In recent years, mixed model assembly lines are gaining popularity to produce a variety of models on the single-model assembly lines. Mixed model assembly lines have two types of problems which include sequencing of different models on the line and balancing of assembly line. These two problems collectively affect the performance of assembly lines, and therefore, current research is aimed to balance the workload of different models on each station, to reduce the deviation of workload of a station from the average workload of all the stations and to minimize the total flow time of models on different stations simultaneously. A multi-objective artificial bee colony (multi-ABC) algorithm for simultaneous sequencing and balancing problem with Pareto concepts and local search mechanism is presented. Two kinds of mixed model assembly line problems are analysed. For the first and second problems, each model task time data and precedence relation data are taken from standard assembly line problems, from operation research library (ORL) and from a truck manufacturing company in China, respectively. Both problems are solved using the proposed multi-ABC algorithm on two different demand scenarios of models, and the results are compared against the results obtained from a famous algorithm in the literature, i.e. non-dominated sorting genetic algorithm (NSGA) II. Computational results of the selected problems indicate that the proposed multi-ABC algorithm outperforms NSGA II and gives better Pareto solutions for the selected problems on different demand scenarios of models.     

基于混合遗传算法的混合装配线排序问题研究

为使混合装配线有效运作,研究了混合装配线的生产排序问题。以装配线上各种零部件消耗速率均匀化和最小生产循环周期最短为优化目标,描述了多目标排序问题,并建立了优化模型。针对基本遗传算法在求解排序问题时的早熟收敛问题,提出一种改进混合遗传算法。该算法借助模拟退火算法思想对适应度尺度进行调整,使遗传进化初期削弱种群中个体适应度差异,而在遗传进化后期强化种群中个体适应度差异,以提高对最优解的搜索能力。同时,根据个体适应度自动调整遗传操作参数,既保存了种群中的优良个体,又不失个体的多样性。最后通过案例分析验证了算法的有效性。     

基于改进分散搜索的混流装配线排序问题

针对混流装配线生产效率问题,设计了以最小化工作站的闲置与超载时间和最小化总调整变换时间为优化目标的数学模型.为得到高质量且平稳性好的解,提出了适应该模型求解的改进分散搜索算法.该算法首次应用一种基于遗传理论的多样性初始解生成法,不但保证了初始种群的多样性,而且为参考集提供了高质量的初始解.设计了参考集生成更新方法、子集产生方法、子集合并方法和优化解方法等多种机制,既保持了种群的多样性,又寻求到了质量较高的满意解.通过某企业混流装配线实例,验证了所设计算法的有效性.     

面向中小企业装配设计系统的产品装配模型

为建立高效的中小企业装配设计系统,定义了多层次与多维度的装配集成模型.为有效实现各项装配设计功能,提出一组装配应用模型,分别对装配拓扑结构、装配关系、装配工艺及仿真等进行建模,自动生成尺寸链、装配关系矩阵与电子技术文档等;采用装配领域模型表达公共语义结构与领域知识,建立单一装配数据源,支持数据重用与共享.研究了装配数据迁移与衍生衍变方法,用以实现面向结构、语义与过程的模型数据自动衍变.将该模型用于AeroAssem装配设计系统的设计开发,并进行了应用验证.     

Sequencing the mixed-model assembly line to minimize the total utility and idle costs with variable launching interval

A mixed-model assembly line (MMAL) is a type of a production line where a variety of products is assembled on it. A mixed-model assembly line problem involves not only solving the traditional problems of the assembly line design (i.e., determining the cycle time, the number and sequence of stations, and the balancing problem) but also determining the sequence of products in assembly line. The product sequencing has a high effect on the mixed-model assembly line efficiency. In this paper, we consider sequencing problem with a variable launching interval between products on the assembly line. A mathematical model is presented, which is capable to solve the small-sized ones of these problems. The considered problem involves two optimization problems (the sequencing problem and launching interval problem). Since this problem is strongly NP-hard, a hybrid metaheuristic algorithm based on the simulated annealing approach and a heuristic approach is developed. The heuristic approach (launching interval between products algorithm) is presented to solve the launching interval problem for each sequence. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. Variable launching interval consideration in MMAL problem causes the higher complexity of this problem. However, this assumption improves the considered goals for this problem. Not only a power algorithm for MMAL is presented in this paper but also the effect of this assumption is discussed. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm.     

基于RFID的混流装配汽车生产线物料动态配送研究

针对混流装配的汽车自动化生产线提出了基于RFID的车辆追踪和基于条码的无线物料库存管理实现方法.在此基础上,设计了装配生产线的物料动态配送调度业务流程,给出了物料动态配送的规划依据,并进行了实例计算.     

基于混合粒子群算法的混流装配线投产顺序研究及仿真

针对混流装配线投产顺序的优化问题,提出两个目标函数.针于这种多目标优化问题,提出了一种混合粒子群算法.该算法结合最优解评估选取方法和遗传算法编码和交叉的思想,对粒子的全局极值和个体极值的选取做了改进.给出发动机混流装配线的一个实例,用该算法求投产顺序,按照求得的投产顺序在AutoMod仿真平台上建立仿真模型.通过仿真运行,证明了该算法求解混流装配线投产顺序的有效性以及AutoMod仿真混流装配线投产顺序的可行性.     

装备维修规划的多目标优化模型和求解算法

为有效地刻画和求解军事装备系统的维修规划问题,建立了一个以维修费用和任务能力为目标的约束优化模型,提出了一种求解装备维修规划问题的多目标禁忌搜索算法.模型考虑了维修器材和工时两种费用指标,并在数质量评估的基础上通过二次回归方程来分层评估装备系统的任务能力指标.算法采用两阶段搜索策略,第一阶段从维修数量下限出发,以任务能力为演化目标进行搜索,直至找到一个可行解;第二阶段以任务能力/维修费用比为演化目标进行搜索,不断改善整个非支配解集.实验表明,算法能够求解型号≥500种,数量≥45 000的大规模问题,模型和算法求解的质量也在实际应用中得到了验证.     

面向现场装配的产品装配工艺模型表达与管理方法

针对面向现场装配的工艺信息完整准确表达与高效管理的应用需求,提出以三维装配过程模型为载体实现面向现场装配的产品装配工艺模型表达与管理方法.分析了面向现场装配的产品装配工艺信息变迁特点,明确了从产品预规划装配工艺信息向现场实际装配工艺信息的实例化映射规则;定义了三维装配过程模型与装配工艺信息数据集,并确定了工艺信息在该模...     

面向卫星总体总装信息的多层级融合模型与管理

针对卫星总体总装信息采用的传统管理模式制约着卫星研制向短周期、高水平迈进的问题,为实现卫星总体总装信息从传统管理模式向信息化管理模式转换,并为全流程数据无缝流转和驱动的卫星智能制造打下基础,在对卫星总体总装过程和信息构成调研分析的基础上,通过抽象、聚类和分层融合,构建了面向卫星总体总装信息的多层级集成融合模型,研究了卫星总体总装信息的信息化管理方法。经多型号卫星试用,验证了所研成果能够满足卫星总体总装数据信息化管理的需求。     

Possibilistic inventory and supplier selection model for an assembly system

In this paper, the problem of inventory lot-sizing and supplier selection for an assembly system is considered, where the supplier available capacities are assumed as ambiguous dynamic parameters. In this scenario, which is a frequent case in large assembly-based factories such as automobile manufacturers, the final product is assembled from multiple components with different conversion factors, which can be sourced from multi-capacitated suppliers through the multi-period horizon of imprecise demand. Due to high shut-down costs of assembly lines, it is assumed that production never stops even though some components may not be available. Therefore, the unfinished products are transferred to a buffer zone and preserved there until the lacking components become available. In this study, a possibilistic mixed integer mathematical model, with fuzzy objective function and soft constraints, is developed to determine which component in what quantities, from which suppliers, and in which periods should be ordered. The model, inspired by the real case of the Iran Khodro Car Company, aims to maximize the profit while keeping a high customer service level by avoiding shortages. This model also considers the ambiguity of dynamic parameters such as demand, suppliers’ available capacities, prices, and holding and shortage costs. To solve the problem, the possibilistic model is first converted into an auxiliary crisp multi-objective model. Through an interactive fuzzy approach, the suggested multi-objective problem is then transformed into an equivalent single-objective model. Finally, a particle swarm optimization is proposed to achieve the overall satisfactory compromise solution. A numerical sample is used to validate the proposed model.