混合型生产行业多视图成本核算模型

在企业资源计划等提供的集成环境中建立了生产成本管理流程,提出批次转换、成本关联批次和批次作业等概念,并应用于物料跟踪和成本统计,以保证成本数据的准确性.根据不同的关注点,分别分析了工序作业和批次作业两类作业的成本库和成本动因,推导出了多视图的成本核算公式.该模型解决了传统成本核算无法准确核算订单成本等问题,并能够为决策、技术创新等行为提供支持.模型在某企业得到应用,验证了其可行性和有效性.     

基于作业成本法的工作流模型性能分析研究

针对以活动网络图为基础的工作流模型,提出了一种基于作业成本法(ABC)的成本性能分析方法,探讨了成本与过程模型元素的关联以及成本动因选择中应考虑的相关性和行为效应等关键要素,着重研究了将成本动因系数相同或具有微小差别的作业动因进行合并的原则,并用数学模型对其合理性进行了严格的证明,然后在理论研究的基础上展示了部分实例在自行开发的工作流模型仿真分析工具中的运行情况,最后总结了本文所提出的分析方法相对于过去分析方法的优势,并展望了未来的可能研究方向.     

考虑排产约束的汽车零部件出库订单排序优化北大核心CSSCI

针对TPL仓库面向汽车零部件企业的产前物料拣选和配送作业环节,研究了JIT生产模式下配送送达时间限定和生产线缓冲库容量有限条件下的出库作业拣选订单排序的优化模型及算法。在分析现有拣选订单排序模式的基础上,提出了融合现有模式优点的新作业模式,建立了该模式下拣选订单排序优化模型,并针对这一整数组合优化模型,设计了一套基于贪心理论的算法对其进行求解。通过实际案例分析表明,该模型及算法可以达到减少拣选作业空余时间、提高作业效率、降低作业成本的目的。     

考虑排产约束的汽车零部件出库订单排序优化

针对TPL仓库面向汽车零部件企业的产前物料拣选和配送作业环节,研究了JIT生产模式下配送送达时间限定和生产线缓冲库容量有限条件下的出库作业拣选订单排序的优化模型及算法。在分析现有拣选订单排序模式的基础上,提出了融合现有模式优点的新作业模式,建立了该模式下拣选订单排序优化模型,并针对这一整数组合优化模型,设计了一套基于贪心理论的算法对其进行求解。通过实际案例分析表明,该模型及算法可以达到减少拣选作业空余时间、提高作业效率、降低作业成本的目的。     

混流生产线车间布置的顺序矩阵方法

为节省混流生产车间的运行成本,通过扩展顺序矩阵模型和分析混流生产线,提出车间布局优化的顺序矩阵方法,并讨论了5种作业关系之间的运算规则,得出普遍适用的作业关系运算规则。     

供应链管理与基于活动的成本控制策略

供应链管理的最终目的是用系统的管理思想最大限度地降低企业产品进入市场的成本。获得最大利润;同时使用户的价值最大化和用户成本最小化。论述了供应链管理思想对企业成本管理的影响,提出了企业三层价值链模型;还探讨了供应链的成本控制模式,提出了用户成本的概念;并探讨了基于活动的作业成本核算的原理和方法,分析了供应链目标成本的确定方法,然后提出供应成本控制的４种控制策略。     

作业成本法的经济生产批量模型

应用作业成本法(ABC)于传统的经济生产批量问题.这一模型不仅考虑了库存补货成本、库存持有成本和缺货成本,同时还考虑了生产批量和生产周期成本.通过Lingo进行数值计算,结果显示新模型优于传统的模型.     

基于作业成本法的医疗物资TCO优化模型

针对传统医疗物资采购主要关注采购价格、忽视医疗物资供应链成本这一问题,提出了一种结合作业成本法(ABC)与总体拥有成本(TCO)理论的医疗物资TCO优化模型。首先,运用ABC详细分析并核算医疗物资供应链成本,如供应商维持成本、质量检验成本、运输成本及手术延期成本等;然后,通过建立医疗物资TCO优化模型优化医疗物资采购策略。最后,通过分析天津市某三级甲等医院医疗物资采购案例,证明本模型可以有效地降低医疗物资采购成本,并为医院成本控制管理提供合理建议。     

残疾人作业调适决策模型及应用

将作业调适分为硬调适和软调适,以成本最小为决策目标,建立残疾人作业调适的定性定量决策模型。基于残疾人动作分析的方法,建立残疾人作业能力差损模型,并以此构建作业软硬调适的成本计算模型,对残疾人的作业调适进行多层次决策。通过实例,对作业能力差损模型进行验证。结果显示,模型的效度及一致性较理想。     

数字化工作流程中自定义作业描述模型的研究

借鉴了JDF作业描述模型"资源链接过程"的设计思想,利用现有的底层功能模块,研究设计了自定义印刷作业描述模型。最后以新模型为基础研发了数字化工作流程软件平台,并测试了模型的应用性。该模型采用XML描述,与JDF相比,自定义作业描述模型的逻辑结构简单,既可满足印刷企业生产流程功能定制的需要,又可大幅度降低印刷数字化工作流程软件的研发成本。     

A New Activity-Based Cost （ABC） Mathematical Model

Along with the product prize competition growing intensely, it is apparently important for reasonably distributing and counting cost. But, in sharing indirect cost, traditional cost accounting unveils the limitations increasingly, especially in authenticity of cost information. And the accounting theory circles and industry circles begin seeking one kind of new accurate cost calculation method, and the activity-based cost ( ABC) method emerges as the times require. In this paper, we will build its mathematical model by the basic principle of ABC, and will improve its mathematical model further. We will establish its comparison mathematical model and make the ABC method go a step further to its practical application.     

Discrimination between accelerated life models via Approximate Bayesian Computation

Accelerated life testing (ALT) is widely used in high-reliability product estimation to get relevant information about an item's performance and its failure mechanisms. To analyse the observed ALT data, reliability practitioners need to select a suitable accelerated life model based on the nature of the stress and the physics involved. A statistical model consists of (i) a lifetime distribution that represents the scatter in product life and (ii) a relationship between life and stress. In practice, several accelerated life models could be used for the same failure mode and the choice of the best model is far from trivial. For this reason, an efficient selection procedure to discriminate between a set of competing accelerated life models is of great importance for practitioners. In this paper, accelerated life model selection is approached by using the Approximate Bayesian Computation (ABC) method and a likelihood-based approach for comparison purposes. To demonstrate the efficiency of the ABC method in calibrating and selecting accelerated life model, an extensive Monte Carlo simulation study is carried out using different distances to measure the discrepancy between the empirical and simulated times of failure data. Then, the ABC algorithm is applied to real accelerated fatigue life data in order to select the most likely model among five plausible models. It has been demonstrated that the ABC method outperforms the likelihood-based approach in terms of reliability predictions mainly at lower percentiles particularly useful in reliability engineering and risk assessment applications. Moreover, it has shown that ABC could mitigate the effects of model misspecification through an appropriate choice of the distance function.     

A multi-objective optimisation approach for order management: incorporating activity-based costing in supply chains

Most of the supply chain order management decision making models proposed in the literature are based mainly on the material flow and capacity constraints without any consideration to the profitability factor. In this paper, we develop a multi-objective mixed-integer programming (MIP) model which considers profitability in order to effectively manage order acceptance decisions in supply chains, subject to capacity constraints by using activity-based costing (ABC). While there are a numbers of decision-making models in literature integrating ABC in supply chains, this study expands the previous models with a more customer-oriented approach. The proposed model fulfils a desirable amount of orders completely and accepts selective number of orders partially with an objective of minimising the amount of residual capacity and increasing the profitability.     

基于人工蜂群算法的车辆主动悬架LQG控制设计

针对2自由度1/4车体汽车悬架LQG最优控制模型,综合局部精英策略局部搜索能力强和人工蜂群算法全局搜索效率高的优点,提出基于局部精英策略人工蜂群算法确定其加权系数的优化方法。利用Matlab/Simulink仿真软件,以积分白噪声模型作为地面输入和单位阶跃输入为路面输入模型,分别将传统LQG控制、人工蜂群算法LQG控制和局部精英策略人工蜂群算法LQG控制进行仿真和对比分析,结果表明,局部精英策略人工蜂群算法LQG控制方法可改善汽车的行驶平顺性和操纵稳定性。     

平面应变情况下多重势面模型与邓肯-张模型的比较

多重势面理论给岩土材料的本构关系研究指出了更开阔的数学背景。由此建立的土的本构模型可以无需推求塑性势函数和屈服函数,且其所能表述的本构关系比通常的塑性位势理论更为广泛。基于应变空间的多重势面模型具有参数求取简单、程序易于实现的特点,更具有实用性。在这篇论文中,利用所开发的有限元程序NM02就平面应变情况对多重势面模型和邓肯-张m-E模型计算成果进行对比分析,其中多重势面模型参数与m-E模型参数完全相同。有关计算分析成果对进一步研究多重势面模型是很有意义的。     

Reliability analysis using an additive Weibull model with bathtub-shaped failure rate function

Lifetime distributions for many components usually have a bathtub-shaped failure rate in practice. However, there are very few practical models to model this type of failure rate function. In this paper we study a simple model based on adding two Weibull survival functions. Some simplifications of the model are also presented. The graphical estimation technique based on the conventional Weibull plot is demonstrated to be useful in this case.     

A comparison of discrete granular material models with continuous microplane formulations

The main objective of this paper is the discussion of two different strategies of simulating the constitutive behavior of granular assemblies. For this, we will focus on discrete particle methods which are widely used in physical science and on continuum–based microplane models which are applied by the engineering community. After deriving the overall constitutive equations based on Voigt’s hypothesis, special focus will be dedicated to the comparison of the relations between the microscopic and macroscopic quantities of each model. It will be demonstrated, that the two basically different modelling techniques lead to remarkably similar results for elastic as well as elasto–plastic material behavior. Received: 19 May 1999     

The Interpretation of Diffuse Reflectance Spectra

Numerous treatments of the diffuse reflecting properties of scattering media have been described. Many theories give an adequate account of the reflectance for a specific set of conditions for which the model was constructed and the solution tested experimentally. Only those models which are considered to be fairly general are considered here.It is convenient to divide the theories into those based upon continuum models and those based upon statistical models. The continuum models typically describe the scattering and absorbing properties of a given medium in terms of two phenomenological constants. These models may all be regarded as varying levels of approximate solution to the general equation of radiative transfer. This provides a convenient basis for comparison of the various theories.The statistical models are based upon a summation of transmittances and reflectances from individual layers or particles. Thus, some assumptions must be made about the nature of the fundamental units, and the validity of the ultimate result will depend upon how closely these assumptions correspond with reality. Only the statistical models lead to expressions from which absolute absorptivities and scattering coefficients can be calculated and related to the actual particle characteristics.The relationship between the various models will be discussed and the features which typify the absorptivity and scattering coefficient according to each will be compared and related to the available experimental data. This leads to a consideration of the characteristics of appropriate model systems and standards.     

Hybridization of ABC and PSO algorithms for improved solutions of RCPSP

A resource-constrained project scheduling problem (RCPSP) is one of the most famous intractable NP-hard problems in the operational research area in terms of its practical value and research significance. To effectively solve the RCPSP, we propose a hybrid approach by integrating artificial bee colony (ABC) and particle swarm optimization (PSO) algorithms. Moreover, a novel structure of ABC-PSO is devised based on embedded ABC-PSO (EABC-PSO) and sequential ABC-PSO (SABC-PSO) strategies. The EABC-PSO strategy mainly applies the PSO algorithm to update the process of the ABC algorithm while the SABC-PSO strategy demonstrates an approach in which computational results obtained from the ABC algorithm are further improved based on the PSO algorithm. In both strategies, bees in the ABC process are entitled to learning capacity from the best local and global solutions in terms of the PSO concept. Subsequently, the updates of solutions are premeditated with crossover and insert operators together with double justification methods. Computational results obtained from the tests on benchmark sets show that the proposed ABC-PSO algorithm is efficient in solving RCPSP problems, demonstrating clear advantages over the pure ABC algorithm, the PSO algorithm, and a number of listed heuristics.     

Updating outdated predictive accident models

Reliable predictive accident models (PAMs) (also referred to as safety performance functions (SPFs)) are essential to design and maintain safe road networks however, ongoing changes in road and vehicle design coupled with road safety initiatives, mean that these models can quickly become dated. Unfortunately, because the fitting of sophisticated PAMs including a wide range of explanatory variables is not a trivial task, available models tend to be based on data collected many years ago and seem unlikely to give reliable estimates of current accidents. Large, expensive studies to produce new models are likely to be, at best, only a temporary solution. This paper thus seeks to develop a practical and efficient methodology to allow currently available PAMs to be updated to give unbiased estimates of accident frequencies at any point in time. Two principal issues are examined: the extent to which the temporal transferability of predictive accident models varies with model complexity; and the practicality and efficiency of two alternative updating strategies. The models used to illustrate these issues are the suites of models developed for rural dual and single carriageway roads in the UK. These are widely used in several software packages in spite of being based on data collected during the 1980s and early 1990s. It was found that increased model complexity by no means ensures better temporal transferability and that calibration of the models using a scale factor can be a practical alternative to fitting new models.