交叉环单向循环搬运系统中交叉环位置的优化

目的为了提高交叉环单向循环搬运系统的搬运量和系统效率,优化交叉环设置位置。方法构建交叉环单向循环搬运系统的数学模型,对设置在不同位置的交叉环进行理论分析,并进行2种不同调度规则下交叉环的设置与搬运量关系的仿真实验。结果交叉环设置在不同位置时,在不同车辆数和不同调度规则的影响下,单位时间搬运量不同。通过理论分析,当交叉环设置于处理站点Sx和Sx+1的中间位置时,单位时间搬运量最多,系统搬运效率最高。结论交叉环设置在最优位置时可增加系统单位时间搬运量,提高系统效率,仿真实验结果证实了理论分析的正确性。     

基于物流关系的BZGF厂厂区布局改进

以BZGF工厂厂区为研究对象,借鉴使用系统布置设计(SLP)方法,通过物料分析和工艺过程的分析,在工厂原有设施基础上设施之间的调整和组合优化来达到最终优化工厂布局的目的.优化目标是有效地利用空间,最大限度地减少物料搬运.以物料搬运量为评价标准,最终布置方案能够大大降低物料搬运量.属于比较典型的设施规划理论在实际问题中的灵活应用,对于设施规划方面的实践工作具有借鉴意义.     

含不一致任务重量的同型熔炼炉批调度优化

为求解含不一致任务重量的同型熔炼炉批调度问题,建立了最小化最大任务完工时间优化模型,设计了一种混合粒子群算法（HPSO）。算法使用随机生成的任务序列作为粒子,采用批首次匹配（BFF）规则对任务序列分批,最长加工时间（LPT）规则将批分配到批处理机,并提出了一种最小完工时间差（MCD）规则对LPT调度结果进行优化;为避免早熟,算法引入交叉和变异操作搜索最优解。通过仿真实验与SA、GA算法对比,实验结果表明算法具有良好的性能。     

平行机系统生产调度与维护计划联合优化

针对平行机系统中生产调度和维护计划的联合决策问题,假设随机故障服从威布尔分布,将作业在设备上加工位置以及设备上预防性维护位置作为决策变量,以最小化最大完工时间和最小化单位维护成本作为优化目标建立了多目标优化模型.建立了基于混合编码的遗传算法,针对不同编码类型采用合适的遗传算子,并引入了自适应交叉和变异概率使算法在收敛速度和求解精度上得到较好平衡.通过与枚举算法对比,证明遗传算法具有较好的时间效率和求解精度.通过与独立决策模型对比,证明联合优化模型能更好地解决联合优化问题,提高企业整体效益.     

基于Plant Simulation的航空综合机加厂房布局仿真研究

科学的生产设置布局规划对航空制造业降低生产成本、提高产品质量尤为重要.以某民用航空发动机传动系统的齿轮和机匣综合加工厂房的规划设计为例,根据厂房设施布置的一般原则,以齿轮和机匣的年产量目标、产品加工工艺、单工艺加工面积需求为设计输入,并考虑各加工区的加工特点而带来的位置约束性,采用遗传算法与模拟退火算法相结合的混合遗传算法为优化工具,将特定的功能区固化在基因串特定的位置上来满足位置约束．计算得出优化方案后,以Plant Simulation为仿真平台,建立该综合机加厂房的仿真模型,从产量满足率、设备利用率、在制品库存量和生产线稳健性等多个指标进行了设施布局的仿真评价．结果表明,优化后的系统能够很好满足生产纲领,各关键设备负载比较均衡,同时维持低水平的在制品库存量,且生产线稳健性较好．因此,综合运用混合遗传算法与Plant Simulation仿真可以为生产设施布局问题给出一种有效、直观的解决方案,且由离散事件仿真获取的评价指标能深刻体现方案的优劣．     

基于空闲时间分配的电压调节策略

为了求解考虑系统能耗的实时动态电压调节（DVS）问题,提出了基于空闲时间分配算法（STDA）的DVS策略,该策略以时间片为单位逐步把所有空闲时间分配给各个任务,且每个时间片都被分配给产生能量减少量最大的任务。分析指出,当时间片大小设置合适时,STDA算法的能耗接近于DVS问题的最小能耗。仿真实验结果表明,对于仅考虑处理器能耗的DVS问题,STDA算法的能耗和最优策略的能耗相近;而对于考虑系统能耗的DVS问题,STDA算法减少能耗的效果要优于其他现有DVS策略。     

工期不确定的模具车间柔性Flow-shop调度问题

由于模具制造属于非重复性单件订货生产,模具加工的任务工期具有较强的不确定性,导致生产调度混乱。为制定合理可行的生产调度方案,建立了任务工期离散概率模型,以最大完工时间的期望值最小为目标,建立不确定工期柔性Flow-shop调度模型;在遗传算法交叉、变异等操作中融入模拟退火操作,将遗传算法的全局搜索能力与模拟退火算法的良好局部搜索能力相结合,设计了不确定工期的柔性Flow-shop调度问题混合遗传模拟退火算法。利用混合遗传模拟退火算法对调度模型进行求解,通过仿真实验表明,该研究对于解决工期不确定的模具车间柔性Flow-shop调度问题是行之有效的。     

随机批量运输的柔性作业车间AGV配置优化

针对柔性作业车间中物料搬运系统的AGV数量配置问题,以最小化AGV购置成本为目标,建立具有系统产出率和生产周期双重约束的优化模型。由于该优化问题是一个随机非线性的整数规划问题,且约束条件无法用决策变量的封闭形式表示,为此,提出一种基于仿真的粒子群优化算法求解该问题。针对具有随机批量运输特征的柔性作业车间,基于离散事件仿真平台构建系统的性能估算模型,提出一种嵌入仿真模型的粒子群优化算法求解AGV数量配置的优化方案。通过仿真算例实验以及不同优化方法对比,对比结果显示,该方法较其他算法在优化结果的优越性和稳定性上分别平均提高了8%和8.9%。分析实际应用案例确定了优化的配置方案,结果验证了所提方法的有效性,具有实际应用价值。     

集成预防性维护计划的单机调度蚁群优化研究

尽管生产调度与预防性维护计划密切相关,且其共有目标都是提高机床的利用率,但是存在着调度优化上的冲突.为了综合考虑单机情形下的生产调度与预防性维护计划,提出了一种改进的蚁群优化算法,用于解决以总计作业加权完成时间和总计维护成本最小为双目标的生产调度与预防性维护计划的集成模型.同时进行了大量的仿真实验,比较结果表明提出的蚁...     

多行多区域车间的设备布局优化设计方法

结合多行多区域车间的特点,进行车间要素定义、设备布局的几何与数学描述。并通过定义包含设备位置点、通道位置点和转向位置点的网络节点以及邻接矩阵,构建设备布局网络模型,给出了设备之间最短物流路径的求取方法与步骤。从而以车间总物流量最小为优化目标,设备布局的干涉为约束条件,建立了多行多区域车间设备布局的优化模型,并引入改进型差分进化算法进行模型求解。最终,以某航空复杂产品生产车间为实例,对提出的优化设计方法进行了验证,给出了设备布局的优化结果和布局设计图。     

Performance evaluation of dynamic scheduling approaches in vehicle-based internal transport systems

This paper studies the performance of static and dynamic scheduling approaches in vehicle-based internal transport (VBIT) systems and is one of the first to systematically investigate under which circumstances, which scheduling method helps in improving performance. In practice, usually myopic dispatching heuristics are used, often using look-ahead information. We argue more advanced scheduling methods can help, depending on circumstances. We introduce three basic scheduling approaches (insertion, combined and column generation) for the static problem. We then extend these to a dynamic, real-time setting with rolling horizons. We propose two further real-time scheduling approaches: dynamic assignment with and without look-ahead. The performances of the above five scheduling approaches are compared with two of the best performing look-ahead dispatching rules known from the literature. The performance of the various approaches depends on the facility layout and work distribution. However, column generation, the combined heuristic, and the assignment approach with look-ahead consistently outperform dispatching rules. Column generation can require substantial calculation time but delivers very good performance if sufficient look-ahead information is available. For large scale systems, the combined heuristic and the dynamic assignment approach with look ahead are recommended and have acceptable calculation times.     

An effective heuristic for adaptive control of job sequences subject to variation in processing times

Variation in sequential task processing times is common in manufacturing systems. This type of disturbance challenges most scheduling methods since they cannot fundamentally change job sequences to adaptively control production performance as jobs enter the system because actual processing times, are not known in advance. Some research literature indicates that simple rules are more suitable than algorithmic scheduling methods for adaptive control. In this work, a ‘state space – average processing time’ (SS-APT) heuristic is proposed and compared to four most commonly used scheduling rules and two well-established heuristics based on Taillard’s benchmarks. It is shown that the adaptive control is made possible under variation in processing times given the flexibility and strong performance of the SS-APT heuristic, especially for work-in-process inventory control.     

汉字的结构布局对现代版式设计的影响与启示

为弘扬传统文化,从书法艺术中寻找适合现代设计的艺术规律,通过对汉字的结构布局图中的布局规律与现代版式设计中的网格设计规律、文字与图片的布局形式的异同点的分析,并根据汉字结构的构形层级推演出版式设计布局图和汉字的半包围结构进行一些版式编排尝试,得出汉字由基本笔画可以组合出不同含义的字,根据汉字的布局规律也一定能设计出独特的版面,由此看出汉字的结构布局规律可以指导现代版式设计。     

Throughput performance analysis and machine layout for discrete-space closed-loop conveyors

In this paper we analyze the performance of discrete-space, fixed-window, closed-loop conveyors. Given the job flow and routing data as well as the configuration of the loop, we first derive the stability condition for the conveyor system. We then address the layout of the stations around the loop. We examine basic tradeoffs with respect to throughput capacity versus the expected Work-In-Process (WIP) on the conveyor for alternative layouts. We show that a layout that minimizes the expected WIP on the conveyor is not, in general, the optimum layout for maximizing the throughput capacity of the system. Last, we discuss the relation between certain conveyor parameters (such as speed and loop length) and system performance.     

Generalized preemption models for single-machine dynamic scheduling problems

In the extensive scheduling literature, job preemption, if allowed, implies that the processing of a partly completed job is temporarily halted and later resumed at the same point. However, little attention has been given to problems where job preemption is allowed under the condition that either some startup time delay must be incurred or some fraction of work must be repeated if preemption occurs. We generalize the notion of job preemption by using models representing these conditions. The models are applied to studying the dynamic single-machine scheduling problems of minimizing total flow time, and of minimizing maximum lateness, subject to arbitrary and unknown job ready dates. On-line optimal dispatching rules, which consider only available - as opposed to look-ahead - information, are developed. These rules determine, on arrival or completion of each job, which available job should next be processed by the machine. A special case of our models, the preempt-repeat scenario, where preempted jobs must be totally repeated, is suggested as heuristic for the equivalent non-preemptive static problem where all ready dates are known and given. A computational study is performed to determine the potential benefits of reducing startup time delays or work repetition fractions in the context of continuous improvement of manufacturing systems.     

Family-based scheduling of shops with functional layouts

Simulation studies of job shop scheduling have typically assumed that either setup times are zero (subsumed within the processing time), or that every part has such a unique setup that no setup advantages can be gained by better scheduling policies. These studies also assume that the shop has exactly one copy of every machine. Some researchers have proposed heuristics that explicitly consider setup times and parallel machines in the context of a one stage shop with static arrivals. In contrast, family-based scheduling centred around setup time reduction has been credited with achieving economic savings in batch production industries where GT is employed. We motivate this study by the case of an existing realworld semi-conductor testing facility that has family setups, parallel machines and dynamic job arrival. Using this setting, we investigate whether benefits can still be obtained by using a family-based scheduling philosophy in those environments which do not permit the physical creation of cellular layouts due to the presence of process related or other constraints. We propose and evaluate two new dispatching procedures in a functional job shop that is modelled after the semiconductor testing facility. Results show that a family-based scheduling philosophy centred around coordinating machine setups is advantageous at relatively high setup to processing time ratios, while classic job shop rules suffice otherwise. Based on these results, we present recommendations for managing such environments. We also suggest future research directions in this area.     

An evaluation of group scheduling heuristics in a flow-line manufacturing cell

When a company adopts cellular manufacturing and creates a cell, one operational problem that must be addressed is how to schedule parts within the cell. Many studies have investigated scheduling rules in a cellular manufacturing environment. However, there has been little consensus on the best scheduling rule to use. To address this lack of consensus, this study evaluated the best scheduling rules from most of these studies in a flow-line cell. The impact of two environmental factors, setup to runtime ratio and number of part families, was also investigated. Out of the five best scheduling rules found, three of these had not been investigated in previous group scheduling studies. The scheduling rule that most often performed best was selecting the part family with the most waiting jobs and sequencing these jobs in shortest processing time order, a relatively simple rule. The more complex rules generally showed poorer performance.     

锡点炉炉温控制设定曲线的确定

在大量试验的基础上，整定出两条锡点炉炉温程序控制设定温度曲线。试验结果表明，用这两条设定温度曲线可获得良好的控制效果。实验中还总结出一套调整设定温度曲线的规则，可为炉温自适应控制提供最基本的调整策略。     

Performance of an ant colony optimisation algorithm in dynamic job shop scheduling problems

The goal of the current study is to identify appropriate application domains of Ant Colony Optimisation (ACO) in the area of dynamic job shop scheduling problem. The algorithm is tested in a shop floor scenario with three levels of machine utilisations, three different processing time distributions, and three different performance measures for intermediate scheduling problems. The steady-state performances of ACO in terms of mean flow time, mean tardiness, total throughput on different experimental environments are compared with those from dispatching rules including first-in-first-out, shortest processing time, and minimum slack time. Two series of experiments are carried out to identify the best ACO strategy and the best performing dispatching rule. Those two approaches are thereafter compared with different variations of processing times. The experimental results show that ACO outperforms other approaches when the machine utilisation or the variation of processing times is not high.