一种新的装备配置优化模型

传统的装备配置优化问题一般采用确定性的数学规划方法解决，难以满足高技术务件下现代战争中需要对大量随机现象和模糊现象进行精确定量分析的实际要求．在分析了高技术条件下装备配置问题一般特性的基础上，根据机会约束规划和模糊机会约束规划的思想，提出了一种新的建立装备配置优化模型的思路和方法，并给出了基于随机模拟的遗传算法的实值算例，算例结果与实际情况基本相符，反映了模型的科学性与实用性．     

极小样本数据的不确定度改进灰色评定方法

为解决经典的测量不确定度灰色评定模型在极小样本条件下的局限性问题，在分析经典模型原理的基础上，引入合成少数类过采样技术(SMOTE)以及支持向量回归(SVR)模型，经过适用性改造，进而提出改进的测量不确定度灰色评定方法。为验证模型的可靠性、泛化性等，分别将计算机模拟数据和某航空发动机高空模拟实验空气流量测量中的总温数据运用到模型中。结果显示，以极差法的计算结果为参考，改进的灰色方法能够适应不同分布类型的极小样本数据，在仿真数据中最高改善41.18%,实例数据中最高改善50.00%。因此，这种改进的灰色方法或可成为解决极小样本数据不确定度评定的有效途径。     

等待时间受限的并行批处理调度问题研究

研究了任务等待时间受限的并行批处理调度问题,建立它的约束规划模型,设计调度任务的“小s大S”规则,该调度规则最重要的参数为临界队长参数和考虑受限时间的紧急时间参数.基于该规则进行模拟实验,用RSM响应面方法进行参数优化,将模拟结果同约束规划模型(CP方法)在CPLEX环境下求得的解进行比较,分析“小s大S”规则的性能和效果.     

基于PGA-ANFIS的露天矿山开采调度系统的实时优化与实践

矿山开采调度系统主要解决不同平台开采的穿孔爆破技术经济参数优化问题。本文以雪峰水泥原料矿山为例,运用自适应模糊推理系统方法构造露天矿山开采调度系统模型,用并行遗传算法解决了不确定环境条件下的复杂矿山开采调度系统模型的优化问题,取得了较好的经济效益。这不仅为生产调度系统的在线优化问题提供了新的思路,而且为穿孔爆破参数的优化提供了新的方法,对促进矿山生产系统的自动化、信息化、智能化、集约化具有重要的参考价值。     

基于PGA-ANFIS的露天矿山开采调度系统的实时优化与实践

矿山开采调度系统主要解决不同平台开采的穿孔爆破技术经济参数优化问题。本文以雪峰水泥原料矿山为例,运用自适应模糊推理系统方法构造露天矿山开采调度系统模型,用并行遗传算法解决了不确定环境条件下的复杂矿山开采调度系统模型的优化问题,取得了较好的经济效益。这不仅为生产调度系统的在线优化问题提供了新的思路,而且为穿孔爆破参数的优化提供了新的方法,对促进矿山生产系统的自动化、信息化、智能化、集约化具有重要的参考价值。     

氯碱工业盐泥综合利用的模糊优化模型及应用

在氯碱工业生产过程中,处理副产品盐泥的最理想办法是将盐泥综合利用,生产盐泥的下游产品。应用模糊理论,建立了盐泥下游产品选择的基于可信性测度的模糊机会约束目标规划模型,并采用两种方法对模型进行求解。当模糊变量是三角模糊数时,将模糊模型转化为确定意义下的清晰等价模型进行求解;在模型推导的过程中,提出了一个引理和一个定理,并给出了其详细的证明过程。对于那些无法转化为清晰等价形式的复杂情况,设计了一种基于模糊模拟的遗传算法,并给出了详细的模糊模拟和遗传算法的步骤。最后通过实例分析证明该建模思想和算法的可行性和有效性。     

模糊环境下考虑供应中断的再制造闭环供应链研究

为研究需求和回收品质量模糊不确定环境下供应中断对再制造闭环供应链的影响,建立了系统总成本模型。运用模糊机会约束规划方法解决模型中不确定性问题,并采用遗传算法和粒子群算法来寻找算例的最优解。结果表明：在不同需求量和回收品质量的水平下企业成本有不同的变化;随着供应中断概率的增加,平均总成本也随之增加。因此,再制造企业在面临需求量和回收品质量模糊不确定的环境时,应尽量避免供应中断,制定符合企业发展的运作计划。     

基于模糊规划的电子废弃物逆向物流网络设计

为了解决回收量不确定情况下的回收网络设计问题,构建了一个基于模糊规划的逆向物流网络模型.采用三角模糊数来描述回收量,利用模糊统计方法计算模糊参数的隶属度,把模糊机会约束清晰化,从而将模糊规划模型转化为确定性规划模型,采用传统求解算法和LING○9.0软件求解.以广西逆向物流网络设计为例,选择电视机、电冰箱、洗衣机、空调...     

模糊环境下再制造系统批量调度研究

针对再制造系统多种不确定因素,包括回收质量、准备时间、加工时间等,研究面向再制造系统的批量调度问题.考虑回收产品存在质量差异的情况,将回收品划分为几种质量不同的工件组类型,各工件组内所有工件的准备时间和加工时间相同,为了减小准备时间和子系统切换时间,将同一工件组内的工件分批量进行调度处理.在满足交货期、加工次序和机器有限等约束条件下,以加权完工时问最小化为目标,建立了模糊环境下的混合整数规划调度模型.该问题包含了工件分批次和调度顺序两个子问题,使用遗传算法进行求解,结合实际算例得出调度策略,验证了该模型在处理再制造生产调度问题上的有效性,并进一步分析了不同批量大小对再制造调度结果的影响.     

基于遗传算法的通信网络可靠性优化设计

在可靠性条件约束下，使网络成本最低是网络规划NP－hard问题，文章提出一种基于遗传算法的优化方法解决了这类问题，仿真结果表明这种算法是有效的。     

A model to examine the effect of loading conditions on scheduling rules in a job shop environment

Although a great deal of research has been carried out in the field of job scheduling this has generally been directed towards examining the benefits of particular rules and presenting improved algorithms. This paper examines how real job shop problems can be modelled and available scheduling rules examined for particular capacity loading conditions. A model of a medium-size production job shop is developed and it is shown that, for their particular shop layout and job mix, the performance and ranking of particular rules with respect to certain criteria, change with shop conditions. The model developed can easily be applied to a wide range of job shop situations and once performance charts have been produced for those scheduling rules available, they can be used to aid the existing scheduling system whether manual or computer based.     

Dynamic job shop scheduling using variable neighbourhood search

In this paper a scheduling method based on variable neighbourhood search (VNS) is introduced to address a dynamic job shop scheduling problem that considers random job arrivals and machine breakdowns. To deal with the dynamic nature of the problem, an event-driven policy is selected. To enhance the efficiency and effectiveness of the scheduling method, an artificial neural network with a back propagation error learning algorithm is used to update parameters of the VNS at any rescheduling point according to the problem condition. The proposed method is compared with some common dispatching rules that have been widely used in the literature for the dynamic job shop scheduling problem. Results illustrate the high efficiency and effectiveness of the proposed method in a variety of shop floor conditions.     

Workshop scheduling using practical (inaccurate) data Part 3: A framework to integrate job releasing,routing and scheduling functions to create a robust predictive schedule

A comprehensive simulation study conducted by the authors investigated the robustness of a predictive scheduling system in a dynamic and stochastic environment. The results revealed that to improve the robustness of a scheduling system, besides using a robust scheduling method with a frequent rescheduling policy, the shop load should be well controlled and kept balanced. Integrating the planning and the scheduling functions has been shown to achieve this objective. This paper discusses the effects of the planning i.e. job releasing and routing and the scheduling functions in creating a robust schedule and a framework to integrate the above functions is proposed. This system consists of a planning module that is concerned with job releasing and routing decisions and a scheduling module that provides the detailed scheduling. A mathematical model using the integer programming technique is use to demonstrate a solution for the planning module. In addition, a heuristic algorithm is used to solve the scheduling problem. It is shown that, in terms of shop load balance level and job delivery time, the proposed system performs better than a benchmark loading strategy on the basis of minimum processing cost.     

Impact of sequence-dependent setup time on job shop scheduling performance

In a production system using multi-purpose and flexible machines, reducing setup time is an important task for better shop performance. Numerous cases were reported about successful reduction of setup times by standardization of setup procedures. However, setup times have not been eliminated and remain an important element of real production problems for production systems such as commercial printing, plastics manufacturing, metal processing, etc. It is especially critical when the setup time is sequence dependent. In this situation, shop performance cannot be effectively improved without the aid of an appropriate scheduling procedure. Review of the past studies shows that there has not been a significant amount of research done on the scheduling procedure for a dynamic job shop with sequence dependent setup times. This paper investigates the job shop scheduling problems that are complicated by sequence-dependent setup times. The study classifies and tests scheduling rules by considering whether setup time and/or due date information is employed. These scheduling rules are evaluated in dynamic scheduling environments defined by due date tightness, setup times and cost structure. A simulation model of a nine machine job shop is used for the experiment. A hypothetical, asymmetric, setup time matrix is applied to the nine machines.     

Look ahead job demanding for improving job shop performance

In this paper a new coordination approach for decentralized job shop scheduling rules is presented and analyzed in a simulation study. The coordination is based on look ahead information and contains a mechanism for demanding and supplying jobs. The simulation experiments show that the performance of conventional scheduling rules is significantly improved using the coordination mechanism.     

装配作业车间分批调度问题的算法对比

建立最小化makespan的装配作业车间分批调度模型,利用遗传算法构建基于整体集成优化策略、分层迭代优化策略和双层进化策略的求解算法。它们的区别在于处理批量划分问题和子批调度问题的联合优化机制不同。最后通过仿真实验对比了几类算法的求解效果和收敛速度,并分析了它们的适应性特点。     

基于规则和仿真的多机并行作业车间生产调度研究

资源分派和能力分派是作业车间生产调度中的重要问题,路径选择规则和分派规则是解决上述问题的有效途径。采用基于规则的仿真研究多机并行作业车间资源分派和能力分派问题,分析工件加工时间、到达率以及机器加工速率对调度结果的影响,以平均完工时间、平均延迟交货率以及平均资源利用率为评价指标,通过对4种路径选择规则和6种分派规则的仿真试验,确定不同性能指标下最佳的调度规则。仿真研究表明:调度规则的选用取决于车间资源配置和调度目标,应避免仅凭借经验或偏好选择规则的调度方法。     

A review of: “Handbook of Industrial Engineering.” Edited by GAVRIEL SALVENDY. (John Wiley & Sons Ltd., 1982.) [Pp.2104.] Price £50

This paper deals with a method for scheduling and control of a maching job shop where the average number of operation stages per part is six and the average operation time per stage is about one hour. The method is based on the adjustment of load balance among machines and the limitation of the amount of work input. By simulation with real data, it was found that two variables, the load balance and input amount of work, definitely influence shop performances such as lateness, mean flow time and utilization of machines. If these two variables are well controlled, good results can be obtained no matter what the dispatching priority rules on the shop floor may be.     

优化交货可靠性的装配作业车间分批调度

装配作业车间生产多规格小批量装配型产品,通常具有差异BOM结构,主要由客制零件组成,但同规格产品仍然包含一定比例的可互用零件,每类零件具有一定批量。此类车间分批调度需要最优化零件类的批次分割和子批加工序列。考虑客户对高交货可靠性的需求,构建了基于最优化交货可靠性为决策优化目标的分批调度数学模型,建立了基于遗传算法和优先级分派规则的混合求解算法。最后通过仿真实验分析和验证了所提方法的有效性。     

Cellular manufacturing: its impact on the total factory

This paper compares a factory structured as a traditional job shop with the same factory structured as a hybrid factory containing a cellular manufacturing unit. The comparison is based on job shop simulation using differing combinations of capacities, allocations of jobs between the cell and the rest of the factory and levels of productivity improvements achieved in the cell. Performance is evaluated in terms of flow times and delays for the cell, the non-cell remainder of the factory and for the normal functional factory. The simulation model was designed to eliminate possible confounding issues of machine reliability, operator skill, unique manufacturer specific part characteristics, factory layout and different scheduling techniques. The result is a systematic evaluation of cellular manufacturing, some general conclusions as to the particular circumstances that favour the use of cells and a set of implications for management practice.