Hierarchical model to design manufacturing systems applied to a metal-mechanic company

This paper describes the application of a model to design and manage the manufacturing process through an integrated system, using a Hierarchical methodology-by means of different aggregation and disaggregation stages with an appropriate time horizon. The hierarchical model obtained allows interfacing between the master schedule and the schedule of the orders. At each level of the hierarchical model some decisions have to be made in order to design the manufacturing system, but having a model that also takes into consideration the management of the system. To do this it is necessary to use aggregated information concerned with the level at which decisions are made. It is obtained from the database, which contains the information at the highest level of aggregation. This model has been applied to a metal mechanic company, that makes final products such as car washers, etc. The benefits of this approach for the company are addressed in this paper.     

THE APPLICATION OF A DYNAMIC FORECASTING MODEL WITH INVENTORY CONTROL PROPERTIES

This article summarizes the application of a forecasting model. Forecasts are made of monthly sales of products which do not change in style on an annual basis. The model is an exponential smoothing model. Adjustments of the parameters of the model are made whenever the average forecast error over the previous four periods is too large to be explained solely by unassignable causes. The efficiency gained in using the model is measured by the ratio of the standard deviation of the forecast errors to the standard deviation of sales. If this ratio is less than one, then the safety stock level that is carried for a given product can be reduced if sales are forecasted with the model and the standard deviation of the forecast errors is used to determine the safety stock level. The net effect is the reduction in the cost of carrying safety stocks. The results of the proposed model are also compared to a similar set of results generated from a basic, exponential model.     

Patient progress modelling and results in Wilm's Tumour

The report describes the development of a mathematical model of the progress of patients with Wilm's Tumour using the methodology developed by Jackson & Aspden [1, 2]. The model incorporates two prognostic factors which are shown to influence patient progress. These are the stage of the tumour and the age of the patient at presentation. The model proved adequate to represent an initial set of patient data, and comparison runs were performed with data from a later time period. These runs highlighted changes in patient progress between the two groups and illustrated the usefulness of the model in this type of analysis. The analysis also underlined the poor prognosis of patients over 5 years old who relapsed.     

带货物权重的车辆路径问题及遗传算法

考虑一个分销中心、多个零售商组成的分销网络系统中具有柔性车辆能力的带货物权重的车辆路径问题.并根据车辆的满载情况采用了不同的运输策略,即单点运输和多点运输方式.在多点运输方式下,与以往诸多研究不同的是,文章建立了一种基于货物权重的VRP模型——WVRP,即在安排车辆线路时每个零售商的货物需求量也作为一个因素考虑,尽可能使车辆优先供货需求量较大的零售商.最后,针对问题的性质,开发了一种基于划分的遗传算法PB-GA对问题进行求解,并与一般遗传算法及常用的启发式算法进行了分析比较.     

基于CVaR约束的多产品订货风险决策模型

过去随机环境下多产品订货往往以期望值作为唯一决策准则,没有将风险控制纳入决策范畴,与实际决策过程不相符合.为给具有不同风险偏好的决策者提供合适的决策分析工具,文章在分析投资组合和产品组合存在某种相似性的基础上,借鉴金融工程领域广泛应用的条件风险值方法,建立多产品最优订货决策模型,并对模型进行了检验,发现它完全符合决策者的直觉要求.而且,由于所建的模型最终可以表示为一个线性规划问题,因此即使是大规模的产品组合问题也可以借助工具软件求解.     

Interpretation of Airborne Asbestos Measurements

Transmission electron microscopy (TEM) is the preferred method of measuring airborne asbestos in buildings, but TEM measurements cannot be used directly in the existing equations relating risk to exposure because the equations are based on measurements made with a different technique--phase contrast microscopy (PCM). Comparison between measurements made by different methods is not simple because the methods differ in the size of particles they can detect, and the relationship between exposure and disease is thought to depend on, among other things, asbestos fiber size. Previous suggestions for converting TEM measurements to PCM equivalents lack generality because they fail to take into account the size distribution of the asbestos particles and the expectation that fiber-size distributions in current nonoccupational environments could differ from the workplaces of the past on which the risk equations are based. A mathematical model is presented for investigating the conversion of airborne asbestos measurements made by one method to an equivalent measurement made by another method. "Equivalent" means having the same potential to cause disease. The model clarifies the issues of concern and suggests approaches for obtaining meaningful conversion factors that will allow TEM measurements to be used in PCM-based risk equations.     

Bootstrap Methods for Markov Processes

The block bootstrap is the best known bootstrap method for time‐series data when the analyst does not have a parametric model that reduces the data generation process to simple random sampling. However, the errors made by the block bootstrap converge to zero only slightly faster than those made by first‐order asymptotic approximations. This paper describes a bootstrap procedure for data that are generated by a Markov process or a process that can be approximated by a Markov process with sufficient accuracy. The procedure is based on estimating the Markov transition density nonparametrically. Bootstrap samples are obtained by sampling the process implied by the estimated transition density. Conditions are given under which the errors made by the Markov bootstrap converge to zero more rapidly than those made by the block bootstrap.     

The acceptance and accuracy of decision analysis methods

This paper reports a field experiment which compared two approaches to decision analysis, called cases and criteria scaling, in terms of their acceptance to users and their predictive features. The case method simulates decisions likely to occur in practice. Each decision is described by particular values of the decision criteria. Experts consider the values of criteria present in each decision and make a judgment. Regression is used to correlate the criteria values with the judgments. The regression equation provides the prediction model. The criteria scaling method decomposes the decision task. Experts weight each criterion and specify how decisions change across levels of each criterion. The predictive model is made up of the sum of each criterion weight multiplied by the criterion-predictor functional relationship. Both methods were applied to build models which predicted the demands for nursing time, using patient severity indicators, for two hospital units. The case method had considerable predictive accuracy and had favorable participant reactions. Predictions made by criteria scaling overestimated needs and this method was viewed as inaccurate and hard to understand by participants. The implications of these findings are discussed.     

带全量价格折扣的供应商最低免运费订货批量研究

本文从供应商角度,首先基于经济订货批量模型建立了使供应商利润最大化的最小订货量优化模型,并给出了解析解。然后,我们又将其拓展到商品带全量价格折扣和运费带全量折扣的情形,并基于折扣函数的非连续性,运用逆向归纳法建立了最优免运费最小订货量的数值算法。最后通过算例对最优免费送货策略的有效性及使用条件进行了理论分析。     

A critical review of end-user information system satisfaction research and a new research framework

This paper presents a critical review of research in end-user information system satisfaction (EUISS). An extensive literature search is conducted from which over 50 EUISS related papers are identified. It is found that the past research is dominated by the expectation disconfirmation approach. To provide more insights into the psychological processing of the information system performance construct and its impact upon EUISS, we propose an integrated conceptual model based on the equity and needs theories. The implications of the proposed model for EUISS are discussed, and suggestions are made for testing the model.     

基于声誉理论的我国经理人动态激励模型研究

本文基于声誉理论,建立了一个关于经理人声誉机制与显性机制相结合的最优动态契约模型,以形成长期激励与短期激励相结合的激励模式,根据分析得出了实现声誉有效激励的条件和提高声誉激励效应的途径,并与没有引入声誉机制的契约模型进行了比较,通过实例验证了声誉机制与显性机制相结合的最优动态契约模型的合理性,对于如何有效地发挥声誉机制对我国经理人的激励作用提出了一些建议。     

Energy modelling for technology assessment: the MARKAL approach

The primary objective of energy policy in many countries is to change the structure of their energy systems so as to reduce the dependence on imported oil. A large amount of funds is spent on energy research and development. The technologies competing for such funds have widely varying characteristics. These relate to costs and benefits, technical performance, environmental effects, the requirements for land, water and materials and the impact on employment. It is necessary to analyse these effects in some detail before decisions on technology programmes can be made. A complete assessment of the possible value of a particular technology cannot be made on an individual basis. It is necessary to consider many technologies simultaneously, competing against each other for various shares of the energy market. However, analysing the behaviour of the entire energy system requires the handling of an extensive amount of data and can only be done effectively with the help of a computerised system. The model, MARKAL, described in this paper is a multi-period linear programming model which has been developed and applied by 15 OECD countries for the purpose of energy technology research and development planning. Examples of the use of the model for this purpose are given both for the group as a whole and for individual countries. The model is structured so that an exogenously specified set of end-use demands must be satisfied given available technologies and energy supplies. The model allows for substitution possibilities in both the energy supply and demand sectors. A feature of the model is the use of varying objective functions such as minimum discounted costs, oil imports, or environmental effluents. These can be used individually or in combination in trade-off situations. The broader question of the use of energy modelling for technology assessment, including its limitations, is also discussed with particular reference to the insights that can be gained from the MARKAL model. Information from the MARKAL model has been used by the International Energy Agency to assist it in formulating a strategy for energy research development and demonstration.     

顾客策略行为下差异产品两阶段定价模型研究

互联网和信息技术的发展,为零售商收集顾客信息带来方便的同时,也使得消费者变得越来越具有策略性和选择性。首先,构建零售商只销售一种高质量产品的情形,研究其两阶段的定价策略,并分析产品的跨期折扣因子对产品的零售价格、销售量和零售商利润的影响。然后,考虑零售商可提供高质量和低质量两种产品的情形,顾客在第一销售期、第二销售期都可以选择两种产品。构建两阶段的定价决策模型,并分析产品的跨期折扣因子、顾客对低质量产品的接受度等参数对产品两阶段的零售价格、销售量的影响。最后,用数值算例分析了第二种模型下顾客对低质量产品的接受度等模型参数对零售商两阶段总利润的影响,然后比较了第一种和第二种模型下高质量产品的零售价格和销售量。研究结论较全面的分析了顾客策略行为对差异产品两阶段销售期的定价决策的影响,为零售商进行定价优化决策提供了十分重要的参考。     

A decision-based approach: application to the automatic design of process planning

The notion of centre of decision presented in this article defines a conceptual and generic model enabling us to represent and use expert knowledge. It is suitable when the problem to be solved can be broken down into a sum of interdependent subproblems. Actions can be planned progressively and previous decisions can he modified by a backtrack mechanism. This principle is iterative. The structure is made up of many independent rules and an action plan. The customization of the application is possible even if the software evolves with future updates. This model has been applied in the LURPA-TOUR software which is a computer-aided process planning system for rotational parts.     

我国企业内部冲突状态的评价测度模型

本文采用Fuzy集合论与AHP法相结合的思路,对企业内部冲突状态进行综合量化测度,建立了一个定量测度我国企业内部冲突状态的数学模型---二级模糊层次综合评判模型。     

How managers decide to use planning models

Recent published reports and surveys have shown that a growing number of corporations and government agencies are using decision models not only for lower level scheduling and resource allocation but also for short-range and long-range planning. Although the literature has described in some detail the types of models used and the ways in which they are used, limited attention has been paid to the ways in which managers decide whether or not to use these models. This paper, which is based on a series of case studies, suggests that the decision to use planning models is made not by performing a comprehensive cost benefit analysis, but by the use of a reference model—that is, an existing model, sometimes in a competitive organization, similar to the one being considered.     

SIMULATION FOR FIRE DEPARTMENT DEPLOYMENT POLICY ANALYSIS

This paper discusses the use of simulation in the determination and analysis of alternative deployment strategies for urban fire supression systems. The simulation model utilizes the New York City-Rand Institute simulator of fire department operations tailored for use with the Denver Fire department. A distinction is made between static deployment (where mathematical programming methods are used) and dynamic analysis (which employs the simulation model). The simulation model is described, as are its extensive data requirements. The results discuss measures of validation of the simulation and outline the recommendations resulting from this research.     

EVALUATION OF MULTIATTRIBUTE ALTERNATIVES: ADDITIVE VERSUS CONFIGURAL UTILITY MEASUREMENT

A model for measuring subjective evaluations of multiple component alternatives is developed and tested in the context of business students' evaluations of professorial candidates for tenured positions. The model is based on a type of ANOVA formulation in which the response variable need only be rank ordered. That is, arbitrary monotonic functions of subjective responses can be made that optimize a well-defined badness of fit measure. Application of the model indicates that metric analysis of the response data can exhibit a large number of configural (interaction) effects that may be a reflection of how subjects use rating scales rather than anything more basic in their combination of multiple component cues. Implications of these findings for the modeling of multiple component choices are discussed.     

Success and failure in management buyouts

This paper outlines a model for examining the process of formulating a successful management buyout, taking the viewpoint of all concerned, viz., buyers, sellers, advisors, investors and employees. It arises out of the observation of, and involvement in, a number of buyout negotiations: some were completed but continue to falter; some were aborted; others are currently successful. The paper suggests that eventual success is a function of two main factors. The first is the probability of conflict, as defined by the buyout typology, and the second the decisions made, and not made, during negotiations. The latter includes such questions as, for the company: what to hive down: which management to involve; future customer relations; and for the deal: the setting of the price: the future role of investors; choosing advisors.     

SPECTRAL ANALYSIS IN BUSINESS FORECASTING*

Although spectral analysis has previously been discussed in a number of business journals, the discussion has not been detailed enough for non-mathematicians. The objective of this paper is to review in detail the concepts and to go over the computations of spectral analysis as they pertain to forecasting. To gain insight into the model building technique of spectral analysis, a passing comparison with a familiar model–regression–is made. Regression analysis attempts to find a set of independent variables that shed some light on the dependent variable to be forecasted. In other words, if the independent variables have some functional relationship with the dependent variable, a reliable forecast of the dependent variable can then be made. Forecasting using spectral analysis, on the other hand, is based on the assumption that the variation of a time series can be explained by some mixture of sine and cosine waves. Model parameters can then be estimated for these waves and forecasts be made. These parameters have the same property of least squares as in ordinary regression analysis. A transformation of these parameters gives the spectra of the time series. The spectra are related to the explained variation present in regression analysis. An extension of the spectra gives a set of coefficients of an autoregressive forecasting model. This latter model is referred to as the Wiener-Kolmogorov forecasting model.