考虑余-废料资源回收的车间物料配送路径规划研究

针对离散制造生产过程中物料配送及余-废料资源回收效率低、成本高等问题,在分析车间物料流循环过程基础上结合物料配送时间窗限制,提出了物料配送和余-废料资源回收协同优化的物料再循环策略,并建立了以车间物料流总成本为目标的物料再循环路径规划模型。利用遗传算法在Matlab软件中对实例进行求解,验证了物料再循环策略应用于离散制造车间物料配送和余-废料资源回收的可行性和有效性。     

基于改进遗传算法的导向辊生产调度方法研究

目的 研究导向辊生产车间中的调度优化问题,有利于缩短工件的完工时间,提高产线生产效率。方法 以某导向辊生产车间为研究对象,以最小化最大完工时间为目标建立数学模型。针对该导向辊生产车间的实际工况,提出一种改进的遗传算法进行求解。通过对10种不同尺寸的导向辊进行生产调度,分别采用改进的遗传算法和传统遗传算法进行试验分析。结果 改进的遗传算法相比传统遗传算法寻优能力更高,工件的完工时间从139 min缩短为113 min,缩短了18.7%左右,生成了完工时间为113 min的生产调度甘特图。结论 与传统遗传算法相比,改进的遗传算法在导向辊生产调度优化中具有更高的全局优化能力和寻优精度。     

考虑运输时间的绿色作业车间调度问题研究

针对制造车间能量消耗大、利用率低的现状,以作业车间为研究对象,建立了一种AGV (automated guided vehicle)运输与加工资源集成调度的模型。首先,通过考虑机器间利用AGV运输工件所需的时间与对应的能耗构建了车间总能耗和完工时间的多目标优化模型,并设置权重系数来调节优化目标的偏好。其次,提出了一种融入模拟退火搜索策略的分布估计算法对模型进行求解。该算法主要是利用分布估计算法全局搜索能力快和模拟退火算法突跳性强的特点构建的一种新的混合算法。同时设计新的退火函数来进一步提高算法深度搜索能力。最后,通过实例验证所提算法的可行性和模型节能的有效性。     

一种面向卷烟混合生产线的优化调度模型研究

目的 基于多品种、小批量的生产制造模式,在规定的8 h工作之内,快速有效地生产出多品种、多批量的卷烟,并对所需物料进行准确调度,达到经济效益最大化的目的。方法 针对某烟草生产企业订单需要生产6种型号的品牌香烟,通过分析卷烟生产线的工艺流程,提出一种解决卷烟厂车间资源优化调度的CSS模型,该模型可以根据产品之间的销售需求情况来匹配生产线资源配置,按需求比采用粒子群优化算法计算出单次投料后混合生产香烟所需的最小时间与最大收益。结果 将所得方案进行综合对比后,计算得出在规定工期内,生产香烟获取利益的最优分配方案,在迭代在10次以内时已完成了优化过程,最大获利为3.65万元。结论 该优化模型通过改变相关工艺参数能够实现对不同混合生产线的资源调度优化,并对其他制造行业提供借鉴价值。     

Modelling and solving algorithm for two-stage scheduling of construction component manufacturing with machining and welding process

This paper focuses on a two-stage machining and welding scheduling problem based on an investigation at a structural metal manufacturing plant, aiming to minimise the total makespan. Several parts processed at Stage one according to classical job-shop scheduling are grouped into a single construction component at the second welding stage. Fabrication of the construction component cannot begin until all comprising parts have been completed at Stage one. This paper establishes a novel mathematic model to minimise the total makespan by mainly considering the dominance relationship between the construction component and the corresponding parts. In order to solve this two-stage problem, we propose an improved harmony search algorithm. A local search method is applied to the best vector at each iteration, so that a more optimal vector can be subsequently realised. The average value, minimum value, relative percentage deviation and standard deviation are discussed in the experimental section, and the proposed local best harmony search algorithm outperforms the genetic algorithm, immune algorithm and harmony search algorithm without local search. Moreover, six optimal solutions are given as Gantt charts, which vividly illustrate that the mathematical model established in this paper can facilitate the development of a better scheduling scheme.     

软件开发项目多技能人力资源均衡调度模型

为了在软件开发项目中同时解决项目活动调度问题和多技能人员指派问题,实现资源均衡分配,本文建立了一个多技能人力资源均衡调度的混合整数规划模型,并以一个软件开发项目为背景开展了算例研究,采用Lingo11软件环境下改良后的分支定界法进行优化求解。优化之后,项目资源强度方差和员工工作量方差大幅度下降。研究结果表明,本文创建的资源均衡调度模型可以显著提高项目周期内员工需求量和员工工作量分配的均衡水平。     

基于改进粒子群算法的高效船体分段制造优化

针对船体分段制造计划通常受到分段装焊场地、作业设备和作业工序等因素限制,以按需拉动、负荷平衡、缩短周期为优化目标,构建了高效分段制造作业计划优化模型。考虑作业优化模型变量离散和非线性问题,采用改进的粒子群算法,对优化模型进行求解。通过对某船厂实例分析,经Matlab编程运行,表明优化算法对提高分段制造产能、缩短建造周期具有较为明显的效果。     

Response to Al-Hakim's note

Storage location assignment and interleaving policy are two closely related problems in warehousing management. This paper addresses the location assignment and interleaving problem at the same time in an automated storage/retrieval system with duration-of-stay based shared storage policy. Based on the heuristics for single command operation, a two-step procedure is developed to solve the problem. A tabu search algorithm is proposed to improve the solution for medium and large sized problems. The computational results indicate that the tabu search algorithm is effective in finding high quality solutions, and efficient in solving large sized problems.     

有模具约束的并行机批量流调度问题研究

大多数调度问题均假设产品以单个或整批的方式进行生产,而实际生产过程中,会把产品分批后再进行生产。但当考虑模具约束时,对如何解决产品分批以及制定合理调度方案的问题,本文以最小化最大完工时间为优化目标,建立了考虑模具约束的并行机批量流调度模型,并提出了一种基于遗传算法和差分算法结合的混合差分遗传算法（DEGA）,实现分批与调度两个问题并行优化。最后通过对算例测试,DEGA算法得到更优的解,证明了该算法的优越性和稳定性。结合实际案例,验证了模型和算法的可行性。     

面向智能制造的数字仓储系统设计

目的 从设计的角度探究如何运用数字仓储系统满足智能制造发展需求的相关理论,以期为制造企业提供智能化生产服务.方法 运用文献研究和典型案例分析法,通过系统架构、管理模块、数据流等方面对数字仓储系统进行全面设计,揭示出数字化仓储技术与装备的功能特点,进而提出数字仓储系统实现路径.结果 数字仓储系统实现了对物料、成品从订单发出到在途、上架、入库、出库全流程的追踪监控,对仓储、物流资源进行了一体化管理,实现了智能制造信息深度自感知、智慧优化自决策、精准控制自执行.结论 在智能制造的大环境下,数字仓储系统能够满足制造企业大规模定制生产要求,具备高柔性的全流程数字化管理模式,助推智能制造进一步发展.     

求解带AGV柔性作业车间调度问题的改进灰狼算法

针对带AGV的柔性作业车间调度问题,以最小化完工时间为目标,考虑AGV在装载站、机器、卸载站之间的有效负载时间和空载时间,构建了数学规划模型。其次,提出一种有效的灰狼算法进行求解,基于该问题特征,设计机器选择、工序排序和AGV搬运的3段编码,有效地保证每个个体均可产生可行解;灰狼算法中改进了关键参数a和E设定方式,有效平衡了算法的勘探能力和局部搜索能力;为进一步提升算法跳出局部最优解的能力,该算法融合了领域搜索等方法。最后,案例测试结果表明,改进灰狼算法在求解带AGV柔性作业车间调度问题中具有优越的性能。     

基于改进NSGA2算法的多目标柔性作业车间调度

柔性作业车间调度问题（FJSP）是经典作业车间调度问题的重要扩展,其中每个操作可以在多台机器上处理,反之亦然。结合实际生产过程中加工时间、机器负载、运行成本等情况,建立了多目标调度模型。针对NSGA2算法收敛性不足的缺陷,引入免疫平衡原理改进NSGA2算法的选择策略和精英保留策略,成功避免了局部收敛问题,提高了算法的优化性能。通过与启发式规则以及多种智能算法进行比对仿真实验,改进的NASA2算法能获得更好的解。用改进的NAGA2算法求解实例,不仅有效地克服多目标间数量级和量纲的障碍,而且得到了满意的pareto解集,进一步验证了该算法和模型的可行性。     

Data mining-based algorithm for storage location assignment in a randomised warehouse

Data mining has long been applied in information extraction for a wide range of applications such as customer relationship management in marketing. In the retailing industry, this technique is used to extract the consumers buying behaviour when customers frequently purchase similar products together; in warehousing, it is also beneficial to store these correlated products nearby so as to reduce the order picking operating time and cost. In this paper, we present a data mining-based algorithm for storage location assignment of piece picking items in a randomised picker-to-parts warehouse by extracting and analysing the association relationships between different products in customer orders. The algorithm aims at minimising the total travel distances for both put-away and order picking operations. Extensive computational experiments based on synthetic data that simulates the operations of a computer and networking products spare parts warehouse in Hong Kong have been conducted to test the effectiveness and applicability of the proposed algorithm. Results show that our proposed algorithm is more efficient than the closest open location and purely dedicated storage allocation systems in minimising the total travel distances. The proposed storage allocation algorithm is further evaluated with experiments simulating larger scale warehouse operations. Similar results on the performance comparison among the three storage approaches are observed. It supports the proposed storage allocation algorithm and is applicable to improve the warehousing operation efficiency if items have strong association among each other.     

数字化车间物料动态配送规划研究

目的 针对数字化生产车间工位物料需求时间的不确定,导致物料配送不准确、不及时的问题,提出一种动态物料配送策略。方法 首先,根据工位关联度和变动时间窗确定实时的配送工位和协同配送工位,设计基于工位排序的动态物料配送路径优化策略。其次,建立以配送成本和时间窗偏离惩罚成本综合最小为目标函数的数学模型。最后,提出并采用系统动力学仿真与蚁群遗传融合算法联合的方法对模型进行求解。结果 模拟算例表明,与静态物料配送优化策略相比,该策略的平均时间成本减少率为30.1%,平均库存减少率为14.86%。结论 该策略能够根据动态时间窗确定配送工位和协同工位,并实时调整配送顺序,实现物料配送的动态自适应性调整,降低总配送成本。融合算法在迭代次数、收敛性、最优解质量方面有明显优越性。     

混合模拟植物生长算法在包装件配送中的应用

目的针对改进模拟植物生长算法(IPGSA)容易陷入局部最优解及其算法运行时间较长,提出混合模拟植物生长算法(HPGSA)来求解带时间窗车辆调度问题(VSPTW)。方法在IPGSA基础上,提出求解包装件物流配送中VSPTW的混合模拟植物生长算法(HPGSA)。改进IPGSA初始调度方案的构造方式,设计求解VSPTW的C-W算法用于构造HPGSA的初始调度方案;改进IPGSA的邻域搜索算子,选择插入搜索算子和互换搜索算子对HPGSA进行邻域搜索;对18个不同规模的Solomon算例进行仿真测试。结果相对于其他智能算法,HPGSA具有更好的求解性能,能够保证VSPTW对求解算法的要求。结论 HPGSA的全局优化能力、稳定性和运行速度均优于IPGSA、遗传算法、蚁群算法和禁忌搜索算法。     

Benchmark generation algorithm for stochastic mixed model assembly shop simulation and optimization

The Operations Research (OR) community have defined many deterministic manufacturing control problems mainly focused on scheduling. Well-defined benchmark problems provide a mechanism for communication of the effectiveness of different optimization algorithms. Manufacturing problems within industry are stochastic and complex. Common features of these problems include: variable demand, machine part specific breakdown patterns, part machine specific process durations, continuous production, Finished Goods Inventory (FGI) buffers, bottleneck machines and limited production capacity. Discrete Event Simulation (DES) is a commonly used tool for studying manufacturing systems of realistic complexity. There are few reports of detail-rich benchmark problems for use within the simulation optimization community that are as complex as those faced by production managers. This work details an algorithm that can be used to create single and multistage production control problems. The reported software implementation of the algorithm generates text files in eXtensible Markup Language (XML) format that are easily edited and understood as well as being cross-platform compatible. The distribution and acceptance of benchmark problems generated with the algorithm would enable researchers working on simulation and optimization of manufacturing problems to effectively communicate results to benefit the field in general.     

考虑疲劳效应的伤员应急手术调度模型及算法

为了解决城市突发事件应急救援中批量应急手术的调度问题,并考虑医生长时间连续手术对手术持续时间和挽救病人生命的成功率带来的恶化效应,提出了三阶段批量手术调度模型,将应急手术调度看作是存在并行机的流水车间调度问题。利用改进的飞蛾扑火算法对应急手术模型进行求解,并通过实证来测试模型和算法的有效性。为了验证算法的性能,将经典飞蛾扑火算法、粒子群算法和布谷鸟算法与其对比,取20次运行结果,得知最大手术完成时间均值中改进的飞蛾扑火算法为最小,调度模型给出的调度方案中,3个救治阶段在时间维度上保持连贯。仿真结果表明,改进的飞蛾扑火算法能很好地求解批量手术调度模型,获得较好的调度结果。     

Integrated scheduling and tool management in flexible manufacturing systems

A multistage algorithm is proposed that will solve the scheduling problem in a flexible manufacturing system by considering the interrelated subproblems of processing time control, tool allocation and machining conditions optimization. The main objective of the proposed algorithm is to minimize total production cost consisting of tooling, operational and tardiness costs. The proposed integrated approach recognizes an important trade-off in automated manufacturing systems that has been largely unrecognized, and which is believed can be effectively exploited to improve production efficiency and lead to substantial cost reductions.     

基于遗传算法的共享助力车调度问题研究

为了减少调度运营成本,减少调度时间,研究共享助力车的调度问题。将助力车调度和电池配送统一进行,考虑载重对燃油调度车的油耗影响,以燃油调度车固定使用成本和耗油成本最小为目标函数,构建助力车重分配的调度模型。通过AP算法对大范围内的电子围栏进行区域划分,确定助力车的服务范围和调度中心选址的基础上,用遗传算法对各个区域分别求解最小成本的路径规划方案。用算例验证了本模型与算法的有效性和可行性。     

An integrated approach to the facilities and material handling system design

The facility layout problem involves the optimal location of manufacturing facilities into a workshop. The classical approach to the layout design is carried out in two separate steps: the first step is the construction of the block layout, i.e. the location of the departments into the workshop, and the second step is the design of the material handling system. The separate optimization of these two aspects of the problem leads to solutions that can be far from the total optimum. In this paper, an integrated approach to the facilities and material handling system design is proposed. Referring to a physical model, named the bay structure , and to a unidirectional AGV system, a genetic approach is proposed to individuate the locations of the departments, the positions of the pickup/delivery stations and the direction of the flow-path. The minimization of material handling cost is adopted as optimality criterion.