基于产出速度的Job-shop型企业生产作业计划与控制方法

借鉴均衡生产思想以及约束理论,提出基于产出速度的Job-shop型企业生产作业计划与控制方法.为及时反映生产过程的瓶颈漂移现象,提出一种基于产出速度确认系统瓶颈的新方法.利用系统的最佳产出速度确定客户订单的投料顺序,并对可能产生的订单堆积提出推平方法.为较好解决存在的计划与调度相脱节问题,提出一种新的调度策略,即平衡产出法则,使作业计划与之相协调.仿真研究的结果证明了方法的有效性.     

航空运输集装托盘脱胶监测成像方法

目的为了提高航空运输集装托盘使用的安全性与经济性,实现航空运输集装托盘脱胶的在线监测。方法研究一种基于优化损伤概率成像的航空运输集装托盘脱胶监测方法,该方法首先将监测区域划分为一个个矩形子区域,然后判别航空运输集装托盘脱胶发生的子区域,其次使用损伤概率成像方法对脱胶进行定位,最后结合脱胶发生的子区域计算出航空运输集装托盘脱胶的位置坐标。结果依据航空运输集装托盘的生产工艺自制了一块试件对该方法进行实验验证,定位距离误差不大于2 cm。结论基于优化损伤概率成像的航空运输集装托盘脱胶监测方法可对航空运输集装托盘脱胶进行不依赖信号传播速度的成像定位。     

基于MPSO的有限缓冲区多产品厂间歇调度问题的研究

研究了以最小化最大完工时间为目标的有限缓冲区多产品厂间歇调度问题,提出了一种基于多种群粒子群优化(MPSO)的间歇调度算法.该算法采用多种群,增加了种群初始粒子的多样性,在每一代子种群并行进化的过程中引入移民粒子,使子种群之间相互影响和促进,避免算法过早地陷入局部最优,提高了算法的全局搜索能力;每代进化后选出子种群中的优秀粒子作为精华种群,并对其进行变邻域搜索(VNS),进一步提高了算法的收敛精度.通过对不同规模调度问题的仿真,以及与其它算法的对比,证明了该算法解决有限缓冲区多产品厂间歇调度问题的有效性和优越性.     

面向供应链的MC计划调度功能模块运作研究

指出了面向供应链的MC生产计划调度过程是由若干协同化的主导子过程共同实现的;同时,每一主导子过程的实现对应于一个主导功能模块的合理设计与运作.分析了各主导功能模块的基本特征及其模式框架;阐述了基于各主导功能模块协同运作的面向供应链的MC计划调度过程实施模式.将对该计划调度问题在理论探索与实践运用方面提供了基础框架,起到了导向性作用.     

基于多代理和遗传算法的协同生产调度研究

针对经典作业车间调度(Job-Shop Scheduling)问题的局限性,结合实际生产情况,提出了基于多代理机制的供应链环境下的企业间的协同生产调度(Cooperated production scheduling)系统的体系结构,结合多代理的灵活性和遗传算法的全局优化性,阐述了一种基于多代理和遗传算法的协同调度系统,并寻求适合于这种供应链环境的优化调度方案.     

带有工艺约束的并行多机调度策略

针对光刻设备组的生产特点,基于最小化加工时间对其调度问题建立了整数规划数学模型,并提出了一种启发式调度策略.运用Extend仿真软件对传统的FCFS和启发式调度策略分别进行仿真,结果表明,启发式调度策略在减少加工时间和提高设备利用率上皆优于FCFS.     

基于灰色机会约束规划的不确定条件下车间作业调度

针对不确定条件下job shop调度问题的约束条件中含有灰色变量,提出用灰色机会约束规划方法解决不确定条件下job shop调度问题,建立了灰色机会约束规划调度模型.同时,使用灰色模拟的方法和手段解决了灰色机会约束规划问题.给出了如何使用灰色模拟技术处理复杂的灰色机会约束以及基于遗传算法的求最优解的过程,并提出用灰色模拟技术结合遗传算法求解生产调度问题中的灰色不确定规划问题.计算仿真结果表明,这种基于灰色机会约束规划的方法处理不确定条件下车间作业调度问题的模型是可行而有效的.     

基于CTPN的自动化仓库系统调度策略研究

针对目前国内外大多数仓库系统调度研究只局限于某一局部问题(或某一子系统)而不能全面考虑整个系统运行状况的问题,在分析已有调度策略的基础上提出了各子系统的优化调度策略,并应用有色时间Petri网(CTPN)进行建模.基于对各子系统的调度特点及其对整个自动化仓库系统的影响的分析,给出了使各子系统能够协调运行的系统整体上的优化调度策略,并采用仿真工具CPN-Tools对调度策略进行了仿真,仿真结果表明,所提出的调度策略可以提高系统的运行效率,可作为研究自动化仓库系统的调度问题的参考手段.     

基于遗传粒子群混合算法的多生产线协调调度

为了求解多目标多生产线调度问题,结合PSO和GA算法的特点,提出了基于协同进化思想的多种群PSOGA混合优化算法(简称MC-HPSOGA).以最小化最大完工时间、最大化生产线利用率和最大化客户满意度为目标函数,建立了多生产线作业协调调度问题的多目标批量调度数学模型,并且设计最小批量动态分批策略,将MC-HPSOGA算法...     

基于粒模型的生产调度简化方法

随着生产调度问题需要考虑的因素不断增多,其求解空间急剧扩大,优化算法的求解难度急剧增加。为了降低求解难度,本文提出了一个基于粒模型的生产调度简化方法。在粒模型中,生产调度所涉及的生产信息被抽象为同一形式的信息粒集合。并在信息粒的基础上构建生产调度问题的求解空间,在求解空间的划分过程中产生新的信息粒和粒层,并缩小了单个求解空间体量,降低生产调度优化算法的难度。通过针对生产调度问题的具体步骤,证明了基于粒模型的生产调度简化方法具有良好的适用性。     

Coordinated scheduling of intercell production and intercell transportation in the equipment manufacturing industry

Intercell moves are caused by exceptional parts which need to be processed in multiple cells. Intercell cooperation disrupts the cellular manufacturing philosophy of creating independent cells, but is essential to lower the costs for enterprises. This article addresses an intercell scheduling problem considering limited transportation capability. To solve this problem, a two-stage ant colony optimization approach is proposed, in which pre-scheduling and re-scheduling are performed sequentially. To evaluate and optimize the interaction of production and transportation, a transportation benefit function is presented, according to which the scheduling solutions are adjusted. The computational results show that the transportation benefit function is more effective than other strategies, and the proposed approach has significant advantages over CPLEX in both the production dimension and the transportation dimension.     

一类求解带随机成本的生产运输问题的线性逼近方法

生产和运输集成计划问题在许多工业工程领域都普遍存在。要给出最优的生产和运输计划就必须考虑实际工业管理过程中存在的不确定性因素。本文研究了生产厂家的生产能力、商家的需求量和单位运输成本等因素为随机变量情况下的产品生产与运输成本问题,建立了该类问题的随机优化模型。在一定的假设条件下,推导了所建模型的确定等价类。基于问题的结构特征,提出了求解生产和运输计划的一种线性逼近方法,数值例子表明该种方法的应用前景。     

A hybrid VNS-HS algorithm for a supply chain scheduling problem with deteriorating jobs

This paper investigates a coordinated scheduling problem in a two stage supply chain where parallel-batching machine, deteriorating jobs and transportation coordination are considered simultaneously. During the production stage, jobs are processed by suppliers and there exists one parallel-batching machine in each supplier. The actual processing time of a job depends on its starting time and normal processing time. The normal processing time of a batch is equal to the largest normal processing time among all jobs in its batch. During the transportation stage, the jobs are then delivered to the manufacturer. Since suppliers are distributed in different locations, the transportation time between each supplier and the manufacturer is different. Based on some structural properties of the studied problem, an optimal algorithm for minimising makespan on a single supplier is presented. This supply chain scheduling problem is proved to be NP-hard, and a hybrid VNS-HS algorithm combining variable neighbourhood search (VNS) with harmony search (HS) is proposed to find a good solution in reasonable time. Finally, some computational experiments are conducted and the results demonstrate the effectiveness and efficiency of the proposed VNS-HS.     

Economic lot and supply scheduling problem: a time-varying lot sizes approach

We study the economic lot and supply scheduling problem (ELSSP) that arises in the distribution and manufacturing industries. The ELSSP involves the simultaneous scheduling of end-item production and inbound transportation of input materials over an infinite time horizon to minimise the average costs of inventory, production set-up and transportation. We present a new methodology based on a time-varying lot sizes approach for the ELSSP. We also provide computational experiments showing that the developed algorithm outperforms the existing heuristic for improved integrated scheduling.     

Synchronized scheduling of assembly and multi-destination air-transportation in a consumer electronics supply chain

The paper studies the problem of synchronizing air transportation and assembly manufacturing to achieve accurate delivery with minimized cost in a consumer electronics supply chain. The motivation for this study came from a major computer manufacturer in a consumer electronics industry that faces challenges in the final stages of delivery of a supply chain. The synchronization problem is decomposed and formulated as two sub-problems, i.e. a multi-destination air transportation allocation problem and an assembly-scheduling problem. The first sub-problem is formulated and solved as an integer linear programming problem. For the assembly-scheduling problem, two solution methodologies using the concepts of forward and backward scheduling are presented. Computational results indicate that the proposed methodologies can achieve considerable cost reduction compared with the existing methodology applied in industry.     

A block transportation scheduling system considering a minimisation of travel distance without loading of and interference between multiple transporters

Material transportation scheduling problems concerning scheduling optimisation have been extensively investigated by researchers in such fields as industrial engineering and management science. Various algorithms have been proposed to solve such problems. However, the majority of these algorithms cannot be applied to a block transportation problem when a shipyard that uses a transporter, a large vehicle employed for moving weight, is considered. In this study, a hybrid optimisation algorithm is proposed for solving a block transportation problem when multiple transporters are used. With regards to the transporters, a minimisation of the travel distance without loading of and interference between the transporters is considered. A block transportation scheduling system is then developed based on the proposed algorithm. The developed system is applied to an actual block transportation scheduling problem of a shipyard. From the attained results, we demonstrate that the proposed algorithm has the ability to effectively solve the block transportation scheduling problems of a shipyard.     

Integrated production scheduling and vehicle routing problem with job splitting and delivery time windows

In this paper, we study a production scheduling and vehicle routing problem with job splitting and delivery time windows in a company working in the metal packaging industry. In this problem, a set of jobs has to be processed on unrelated parallel machines with job splitting and sequence-dependent setup time (cost). Then the finished products are delivered in batches to several customers with heterogeneous vehicles, subject to delivery time windows. The objective of production is to minimize the total setup cost and the objective of distribution is to minimize the transportation cost. We propose mathematical models for decentralized scheduling problems, where a production schedule and a distribution plan are built consecutively. We develop a two-phase iterative heuristic to solve the integrated scheduling problem. We evaluate the benefits of coordination through numerical experiments.     

Research on rush order insertion rescheduling problem under hybrid flow shop based on NSGA-III

Rush order insertion is widespread in the enterprises that apply make-to-order production mode which affects the stability of production system. This article studies rush order insertion rescheduling problem (ROIRP) under hybrid flow shop (HFS) with multiple stages and multiple machines. A mathematical model simultaneously considering constraints such as lots, sequence-dependent set-up times and transportation times with objectives to minimise makespan, total transportation time and total machine deviation between the initial scheduling plan and the event-driven rescheduling plan is developed and NSGA-III is applied to solve the problem. Three groups of experiments are carried out which verify the suitability of NSGA-III for HFS scheduling problem with multi-objective and multi-constraint, the effectiveness of NSGA-III for the proposed ROIRP and the feasibility and effectiveness of the proposed model and algorithm in solving the ROIRP of a realistic ship pipe parts manufacturing enterprise.     

Book review of Global Strategic Management,by P. Lasserre,Palgrave Macmillan,Basingstoke, 2003, xx + 454 pp., £24.99, softcover (ISBN 0 333 79375 7)

This paper considers the simultaneous scheduling of material handling transporters (such as automatic guided vehicles or AGVs) and manufacturing equipment (such as machines and workcentres) in the production of complex asembled product. Given the shipping schedule for the end-items, the objective of the integrated problem is to minimize the cumulative lead time of the overall production schedule (i.e. total makespan) for on-time shipment, and to reduce material handling and inventory holding costs on the shop-floor. The problem of makespan minimization is formulated as a transportation integrated scheduling problem, which is NP-hard. For industrial size problems, an effective heuritsic is developed to simultaneouly schedule manufacturing and material handling operations by exploting the critical path of an integrated operation network. The performance of the proposed heuristic is evaluated via extensive numerical studies and compared with the traditional sequential scheduling approach. The superiority of the integrated heuristic is well documented.     

A coordinated algorithm for integrated production scheduling and vehicle routing problem

In this paper, the integrated production scheduling and vehicle routing problem is considered for a Make-to-Order manufacturer, who has a single machine for production and limited vehicles with capacity constraints for transportation. The objective is to determine production scheduling and vehicle routing, which are two interacted decisions, to minimise the maximum order delivery time. A property on optimal production sequence is proposed first, based on which backward and forward batching methods are developed and are embedded into a proposed genetic algorithm. The proposed genetic algorithm is capable of providing high-quality solutions by determining the two decisions simultaneously. For comparison purpose, a two-stage algorithm is developed, which decomposes the overall problem into two successively solved sub-problems. The experiments show that the proposed genetic algorithm can provide higher quality solutions than the proposed two-stage algorithm and two published algorithms studying related problems.