Critical evaluation of simulation studies in maintenance systems.

The purpose of this paper is to examine how far simulation studies of maintenance systems are neglecting simulation-related statistical issues. This negligence may leave simulation results suspicious and hard to explain. Several simulation factors are used to identify the strength of executed simulation experiments and to evaluate the level of clarity and reliability of the simulation models. The factors includes purpose of simulation, simulation model, model assumptions, distribution and random variables, simulation languages and computers, program verification and model validation, design of experiment, and analysis of the output. For this purpose, the literature is reviewed and subjected to the evaluation. It is observed that most papers define clearly their objectives, simulation languages, and model performance measures. However, verification, validation, experimental design, and output analysis are the most unclear factors.     

THE DOLLARS AND SENSE OF SIMULATION

This paper deals with the economics of computer simulation applied to problems in the operations management/industrial engineering area. First, the material in the literature dealing with the economics of simulation is summarized. However, the amount of information available on the economics of simulation is very small. A number of hypotheses are presented for this paucity of material. Since many managers operate in an environment in which costs and benefits are relevant to their decision-making process, the lack of data on the economics of simulation may be a barrier to the utilization of the technique. In an attempt to improve this situation, a framework for the collection and specification of the economics of simulation modeling projects is proposed as a method of urging management scientists to begin to collect and publish data on the economics of simulation projects.     

EMPIRICAL INVENTORY SIMULATION: A CASE STUDY*

An empirical simulation was used to investigate the economics of minimum-buy policies in the U.S. Army management of spare-parts inventory. An empirical simulation makes use of historical data as direct input to the simulation rather than randomly generated data based on a characterization of the historical data. Empirical simulation alleviates the drawbacks of characterizing historical data with a theoretical distribution; however, because steady-state conditions are not reached, a methodological problem arises in the evaluation of inventory assets at the end of the simulation. Our solution was to minimize this problem by use of a cyclic approach.     

A survey of simulation modeling techniques in production planning and control (PPC)

The manufacturing sector as a whole has undergone remarkable changes in terms of scale, complexity and technology over the past decades and this applies across most modern high-technology manufacturing such as electronics, semiconductor, aerospace and automotive industries. In order to remain competitive, manufacturers have to produce high-quality products at low cost, and at the same time retain sufficient flexibility and to meet rapidly changing customer demands. Production planning and control (PPC) is a key role which enables the manufacturer to gain visibility and control over all aspects of manufacturing activities. PPC in itself forms a subject of study, within which simulation techniques have proven themselves to be one of the most practical methodologies available to investigate and evaluate manufacturing issues. In this review paper, we focus on state-of-the art applications of simulation techniques in PPC to demonstrate their applicability to modern manufacturing issues. The review reports on academic publications on simulation applications in manufacturing from 2002 to 2014, incorporating surveys of peer-reviewed literature. The review covers three types of simulation techniques (system dynamic, discrete event simulation and agent-based simulation) and eight PPC issues (facility resource planning, capacity planning, job planning, process planning, scheduling, inventory management, production and process design, purchase and supply management). Literature survey is analysed on the basis of simulation application to PPC problems which can give a guideline for simulation technique selection and also can help for simulation modelling in PPC problemsWould you consider changing the term “modeling” to “modelling” in the title. Please check, and correct if necessary.     

基于Kuipers定性仿真算法的多议题谈判模型研究

本文结合谈判问题的相关研究,应用Kuipers的定性仿真算法对多属性谈判问题进行了仿真,仿真过程符合谈判的逻辑和人们的直观推测,能够清晰反映谈判的变化趋势,该定性仿真谈判模型对具体谈判问题具有更强的适应性,解决了传统定量仿真中由于不确定性产生的问题,能够为谈判各方的决策提供有力支持。     

群体行为集成化知识描述与定性模拟研究

针对群体行为变化过程的定性模拟问题,利用定性因果推理和QSIM算法的思路,研究了与人群行为有关的知识描述方法,包括对外部环境、内部文化环境、管理措施、人群内各要素状态、各要素相互关系的描述。然后设计了定性模拟的规则和算法步骤。将上述方法用于一个群体行为变化实例的模拟,模拟结果表明,本文所提出的方法能够较好地解决复杂管理系统的定性模拟问题,所得结果符合实际情况和相关的组织行为理论。     

基于公理设计理论的仿真软件评价方法研究

针对仿真软件评价优选问题,提出一种基于公理设计理论的仿真软件评价方法。以公理设计理论为指导建立仿真软件评价模型,通过信息公理以信息量大小为测度来度量仿真软件产品的优劣。考虑到备选方案评价指标信息具有不完全性和模糊性特征,采用信息公理中的经典信息量计算方法存在局限性,对信息公理中的信息量计算方法进行拓展,提出基于单值点、区间数相离度、满意度和模糊信息的信息量计算方法。结合经典的和拓展的信息量计算方法,给出仿真软件评价流程。以某生产制造企业选择仿真软件产品为例,说明所提出方法的可行性和有效性,实验结果也揭示了在仿真软件商业领域竞争中软件质量起到至关重要的作用。     

面向定性模拟的企业市场营销决策知识描述、学习及处理方法

为了将定性模拟技术用于管理决策领域,研究了基于定性因果关系图的市场营销决策过程的知识描述方法、以及知识学习方法,设计了学习算法步骤。然后,基于这种知识描述方法,以产品的市场占有率为目标,设计了企业市场营销策略选择过程的定性模拟步骤。最后,提出并设计了在市场竞争对抗过程中,企业与竞争者的营销策略选择过程的定性模拟方法和模拟步骤。本文用计算机模拟语言Arena5.0实现了上述算法及模拟步骤,实验表明,本文所提出的面向定性模拟的企业市场营销决策知识描述、学习及处理方法、以及所设计的学习算法和模拟步骤是可行的。     

The Use of Stochastic Simulation in Knowledge-Based Systems

Knowledge-based systems support the decision-making process with the help of domain specific knowledge bases. The knowledge bases almost always have uncertainty associated with them. A variety of approaches have been proposed in the artificial intelligence (AI) literature for the construction of and reasoning with uncertain knowledge bases. Building on this stream of research, we focus on how stochastic simulation can be used to construct and reason with knowledge bases that have uncertainties. An advantage of the simulation methodology is that it may not have to make many of the assumptions made by other approaches. It also allows the designer of the knowledge-based system to control the methodology based on accuracy and time requirements. The simulation approach to knowledge base construction is a modified version of the concept induction procedure used in AI. However, it incorporates, as does simulation modeling, statistical tests to identify the best rule that describes the relationship among the variables. We show that when simulation is used to reason with uncertain knowledge bases, under certain conditions, the number of simulation trials needed to achieve a given level of accuracy is independent of the characteristics, such as the size, of the knowledge base. Empirical results obtained from an experiment confirm our theoretical results and provide evidence that simulation methodology is practical for real life knowledge-based systems.     

Computer Simulation Success: On the Use of the End-User Computing Satisfaction Instrument: A Comment

This comment is part of a comprehensive study to develop a contingency model of simulation success. The current study focuses on the psychometric stability of the end-user computing satisfaction (EUCS) instrument by Doll and Torkzadeh (1988) when applied to users of computer simulation. Using a survey of 411 users, the researchers provide evidence that the EUCS instrument is a valid and reliable measure of computer simulation success. Given this evidence, managers and simulation software product developers can confidently apply the instrument in the investigation of competing tools, features, and technologies.     

考虑观察成本的秘书问题仿真实验研究

针对具有观察成本的秘书问题,分析了决策策略和观察成本对决策结果的影响,并在此基础上提出了柔性标杆和可变观察成本;阐述了仿真试验的理论假设和设计,通过仿真试验考察了观察成本与柔性标杆的不同变化对仿真结果的影响;给出了对仿真结果的分析和探讨。仿真结果验证了理论假设的合理性。     

Automated simulation modelling and analysis for manufacturing systems

Simulation is extensively used as a basis for the analysis and design of manufacturing systems. It has been steadily increasing in popularity due to the simplicity and ease of model understanding even by the non-simulationist. The popularity of simulation is also due to recent developments of easy-to-use simulation software. Simulation generators represent a significant trend in this direction. More recent developments include simulation expert systems both from the viewpoint of modelling and also statistical output analysis. The work that has been explained herewith is based on one such simulation generator that has been developed at the Center for Manufacturing Productivity and Technology Transfer at Rensselaer Polytechnic Institute. This system, RENSAM (RENssclaer Simulator for Automated Manufacturing) is an adaptive simulation generator and has an underlying structure that represents a FMS. The research that has been accomplished is the result of the constant efforts that are being undertaken to make RENSAM a complete decision making tool. In order to achieve what is envisioned, output analysis, optimization and sensitivity analysis routines have been added to the generic simulation and intelligent front end (IFE), The output analysis routine determines the experimental conditions under which the simulation is executed. The optimization routine searches for the optimal values for the parameters of interest and then sensitivity analysis is used to examine the relationship among various parameters. The sensitivity analysis that is presented has been developed taking into account various methodologies in this field.     

METHODOLOGICAL ANALYSIS THROUGH SYSTEMS SIMULATION

Simulation techniques are widely used for analyzing the policy decisions of managers. This paper presents a “higher-level” use of simulation to analyze the modeling decisions of analysts, which models are, in turn, useful for policy analysis. Methodological systems simulation (MSS) is described in terms of a systems performance prediction problem. The MSS program is outlined and the two major uses of MSS-evaluation of alternative models and simulation of the analyst–are described in terms of the results of simulation runs using the systems performance prediction context.     

企业群体行为变化的定性模拟研究

利用定性模拟技术在处理不完备知识和深层知识等方面独有的优势,将定性模拟技术应用于企业群体行为的研究,为复杂管理系统的研究提供了一个有用的工具。针对一个群体工作过程模型,结合专家知识、概率分布设计了模拟规则并进行了模拟,模拟结果比较符合实际。     

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.     

微观分析模拟及其新的支撑平台

本文主要讨论经济政策模拟的新技术──微观分析模拟及其新的支撑平台。首先介绍微观分析模拟的基本原理及构模技术,接着指出它的特点和存在的突出问题,然后分析微型计算机软硬件的飞速发展及对微观分析模拟的支持。最新的事实表明,微型计算机已发展成为微观分析模拟强大的支撑平台。     

基于多智能体的城市群政策协调建模与仿真

以城市群多政府互动与政策偏好演化为例,通过概念模型、数学模型和计算机模型的完整建模过程构建一个多智能体仿真模型,基于动力系统理论构建微观决策主体的偏好演化机制,基于复杂网络模型模拟宏观社会网络的拓扑演化规则,并对仿真模型和模拟结果进行效度和信度的检验。模拟实验探讨了全局交互周期比例、局部交互连接概率、行政/激励调控措施及其交叉作用对城市群政策协调演化的动态影响,并结合大样本模拟数据的统计分析,为促进城市群协调合作和区域一体化进程提供决策依据和政策参考,是多智能体建模与仿真(ABMS)在公共管理和政策领域的前沿拓展,提供了新的研究视角和方法论体系,也是政府组织模拟实验研究(行政学科计算化与实验化)的一次新尝试。     

Logistic Game™: learning by doing and knowledge-sharing

The aim of this article is to define a new simulation game in operation management called Logistic Game?. The main objectives are to introduce a new simulation game approach in solving the different correlated subsystems based on ‘visual interactive learning’ and to verify its positive effects on the learning process with respect to the usual simulation games. The game is based on an inside plant virtual supply chain simulation and copes with the educational challenges of teaching Industrial Logistics in a new, effective way. By applying a visual interactive simulation package, the game creates a virtual dynamic scenario directly visible by participants, with an improvement of experimentation and conceptualisation phases, and offers several logistic decisions and their strategic links from a holistic point of view. The challenge goes beyond a pure theoretical setting and students learn strategies and gain experience directly by operating in a virtual supply chain and sharing knowledge. The Logistic Game has been used to train more then 300 students since December 2006 in three different Italian workshops and has been designed to encourage the employment selection process by the companies involved.     

Visual interactive simulation an aid to decision making

This paper describes a technique of visual interactive simulation. The technique allows a simulation model to be dynamically displayed on a visual display unit. The user can watch the model progress through time and has the ability to stop, interact and try alternative decision strategies. The paper shows that by watching a simulation model progress through time and having the ability to interact with it, a user can improve his analysis and understanding of the original problem situation.