风险管理软件CrystalBall使用指导

合集下载

crystal_ball_软件教学

crystal_ball_软件教学
Crystal Ball模拟基础教程
13-4
报童佛莱迪
➢ 佛莱迪在某大城市里主要市区经营一家报摊。
➢ 佛莱迪贩卖各类的报纸和杂志,其中最贵的报纸为财 经日报 。
➢ 财经日报相关的成本资料:
– 每份报纸的成本为1.50美元 – 每份报纸的售价为2.50美元 – 没售出的报纸,每份报纸可以获得0.50美元的偿还金
➢ 财经日报的销售资料:
– 佛莱迪每天的销售量介于40到70份之间。 – 销售数量介于40到70份之间任何数值的频率相同。
13-5
运用仿真之电子表格模式
13-6
CrystalBall的应用
➢ 利用CrystalBall来进行计算机仿真有四个步骤:
1. 定义随机输入栏。 2. 定义输出栏来预测。 3. 设定执行偏好。 4. 执行模拟。
某一事件发生次数之分配:二项分配
➢ 描述在固定试验次数内的事件发生次数(如:丢10次铜板出现正面的 次数)
➢ 每次试验只有二种可能结果 ➢ 试验相互独立 ➢ 每次试验的机率相同
13-62
直到某事件发生的试验次数:几何
➢ 描述事件发生前的试验次数(如在转轮盘赌局中获胜前的下注 次数)
➢ 每次试验的机率皆相同 ➢ 成功前不能停止 ➢ 试验次数不限定
13-56
具有三个参数的分配:韦伯分配
➢ 某数值(位置)以上的随机数值 ➢ Shape(形状参数)> 0(通常 ≤10) ➢ Shape < 3会太过正偏态较(小于平均值的机率较大),类似
指数分配(當Shape =1时与指数分配相等) ➢ 当Shape =3.25时为对称形,超过这个数值为负偏态 ➢ Scale(规模参数)定义宽度
13-53
一种常用集中趋势分配:对数常态分配

风险管理工具_CrystalBall在企业经营风险管理中的应用

风险管理工具_CrystalBall在企业经营风险管理中的应用

3.7 决策表(Decis ion Table) 决策表是用来表示当决策变量取
定义第 2 年 ~ 第 5 年的累积税后利润为预测变量是类似的。
不同的值时,选定的目标预测变量均值的变化。
271
例如,模型中有 2 个决策变量:“前两年生产线数量”和“后三年 新增生产线数量”。在运用决策表之前,需要先定义这两个决策变量。
图 12 生成决策表的第 2 步:选择决策变量
图 10 定义决策变量“后三年生产线数量”对话窗口
在图 10 中,输入变量名,选择变量上下界(Variable Bounds), 下界 (Low er) 为 1,上界 (Upper) 为 3。选择变量类型(Variable Type)为“离散(Diccrite)”,输入步长(Step)为 1。
很多,如财务风险、时间风险、人身伤害风险、名誉风险等。有的风险 年生产线数量 (B2)×固定资产折旧率 (B8);后三年固定资产折旧
可以度量,有些则难以度量。在企业经营中,财务风险是最常见的,财 (D23~ F23)=(前两年生产线数量(B2)+ 后三年新增生产线数量(B3))
务风险通常可以度量。风险的来源是事件的不确定性,不确定性越 ×固定资产折旧率(B8);税前利润(B25~ F25)= 销售收入—生产成
和销售的产品为某种原料,根据预测,这种原料的需求量第 1 年为 布、泊松分布等多种随机变量的分布。为了简化例子,我们假定模型
20 吨,以后每年增加 2 吨。引进这种原料生产线的建设投资为每条 中所有的随机变量都服从正态分布。它们的均值就是相应数据单元
30 万元,每条生产线的生产能力为每年 7 吨。如果开工生产线太少, 格的值,标准差等于均值的 10% 。
Crys tal Ball 是美国 Decis ioneering 公司开发的,它提供了项目 积税后利润都是负值,第 4 年的累积税后利润首次为正值。即该企

CrystalBall实验操作过程教学教材

CrystalBall实验操作过程教学教材

C r y s t a l B a l l实验操作过程Crystal Ball实验操作过程实验一:一、数据录入与导入双击CB快捷方式图标或直接打开Excel打开软件。

前面提到过Crystal Ball 软件是在Excel里的一个插件,所以双击打开后是Excel的界面,如下图:图 1用户可以在该界面中直接录入数据,也可以左击右上角的符号,选择打开,将原有Excel表格中的数据直接导入到带有Crystal Ball插件的电子表格中。

二、拟合分布图2(1)对数据进行标准化处理(减少原数据相互间的距离对拟合分布的影响)通过Average计算每个分布工程样本数据的均值,然后各个样本数据除以相应的均值,对数据进行标准化处理。

(2)拟合分布选取表格区域,点击工具栏上“Run-Tools-Batch Fit”,如图3所示。

图3在操作对话框中,选择“next”,至图4对话框对相应命令进行选择,可得到拟合过程的相关数据。

图4注:对于卡方检验,水晶球软件计算p值,p值大于0.5一般表示紧密拟合;对于科尔莫格洛夫-斯米尔诺夫检验,一般地,小于0.03的K-S值表明良好拟合;对于安德森-达林检验,小于1.5的计算值一般表明拟合优良。

实验二:一.按照实验一的操作,先将数据在Crystal Ball软件打开.二、假设单元格概率分布的定义及相关操作输入数据后,进行随机变量假设单元格概率分布的定义。

这里假设使用悲观时间的单元格来进行概率分布的定义。

(注:对于假设单元格的选择,并无太多的限制,因为定义各种概率的分布,是由相应的参数确定的,因此选择的假设单元格不同对结果并没有影响。

)有一点需要注意的是,选择假设单元格时,该单元格应当是一确定的数字,而不能是公式.选定单元格(如单元格I2)后,点击工具栏上的,随即弹出图5,CB 软件中提供22种不同的分布可供选择,根据实验任务书的要求,第一和第二项分部分项工程服从三参数beta分布,因此,选择BtaPERT分布,并填入相应参数,即可完成对“基坑支护挖土方”的定义,如图6所示。

量化风险管理(2)-水晶球软件工具使用

量化风险管理(2)-水晶球软件工具使用

/s/blog_493a8455010099wg.html量化风险管理(2)-水晶球软件工具使用CMMI四级里面对风险的量化分析,和基于量化数据的改进是很重视的。

前面我们谈到过当我们确定要改进一个目标的时候,比如缺陷密度DD,我们首先要确定有哪些因子会影响到缺陷密度,分析出来后需要根据历史数据进行相关性分析,分析完成后即可以建立起PPM 的预测模型。

比如我们可以得到关于缺陷密度的预测模型为:Defect Density = 389 + 2.12RV + 5.32DC – 24.1QCRV - 需求的不稳定性。

DC - 设计的复杂度。

QC - 评审和Review等坚持工作的有效性。

有了这个模型后,我们就可以结合我们的目标来寻找如何去改进。

比如我们现在的目标是期望在90%的概率的情况下,缺陷密度都能够控制在<0.35的范围内。

根据现在的历史数据我们可以得到如下的各个因子的分布区间:有了这个数据后我们就可以按照水晶球软件对我们期望的DD值进行蒙特卡洛模拟。

该软件的下载地址为:/。

我们只需要对三个影响因子的概率分布进行简单的设置,对需要模拟的目标进行设置后,系统就会自动的根据概率分布进行1000次的模拟。

通过模拟后我们可以得到下图:可以看到在90%的概率下,现在能够保证的是缺陷密度DD是<0.42。

没有达到我们的要求。

因此我们必须对三个影响因子进行改进,可以是调整均值,也可以是调整其标准差。

究竟是调整哪个因子,我们可以通过因子的敏感性分析来确定究竟哪些因子对目标的影响最大,如下图:通过该图我们可以调整对目标影响较大的QC,调整完成后我们再进行模拟看是否目标已经达到我们的要求。

达到要求后我们就可以得到具体的QC的改进目标,比如QC需要调整到(7,10)的范围内,最可能值在8左右才能够满足我们对目标的需求。

分享到新浪微博已投稿到:排行榜圈子阅读(625)|评论(3)|收藏(1)|打印|举报前一篇:时间管理的核心是什么后一篇:新浪博客新版本的几个有意义的改进_ad_新浪广告共享计划评论重要提示:警惕虚假中奖信息,点击查看详情免费任选1000款游戏新手卡[发评论]人月神话:2008-04-18 23:30:02评论测试!∙厚积薄发:2009-07-14 15:46:03数据假的啊根据Defect Density = 389 2.12RV 5.32DC – 24.1QC和各变量取值 DD最后结果肯定大于196∙厚积薄发:2009-07-14 15:54:09呵呵公式需要除以1000发评论你的Windows 7 你做主新浪产品部优厚待遇聘英才!。

水晶球软件初级教程

水晶球软件初级教程

水晶球软件2000专业版(CrystalBall2000ProfessionalEdition)初级教程摘要加载在微软公司(Microsoft)的电子表格软件(Excel)上的水晶球软件2000专业版(CrystalBall2000ProfessionalEdition)是一个易于使用的软件。

它可以帮助你分析与你的电子表格模型相关的风险和不确定性。

这个软件包括蒙特卡洛模拟(水晶球)、时间序列预测(水晶球预言家)、最优选择(优化查询)和用来构造定制界面和程序的开发工具箱。

由于电子表格缺乏设计和分析可选方案的能力,所以仅用电子表格来估算一个事件发生的概率是不合适的。

而加载了水晶球软件的电子表格模型就能具备这样的功能,从而帮助用户洞察模型运行和结果产生的机制。

本初级教程通过一个媒体产业的实例来演示蒙特卡洛模拟和时间序列预测工具如何用于一个电子表格模型,为商业决策的内在风险提供更深入的了解和度量。

1序言1.1电子表格模型和风险分析风险就是不确定性,是指发生损失、危害和其它不愉快事件的可能性。

大多数人偏好低风险,期待成功、收益或其它形式获利的较高概率。

举例来说,如果下个月的销售超过一定数额(一种令人愉快的事件),那么这些订单会使存货减少,从而导致商品运送的延迟(一种令人不愉快的事件)。

反过来,商品运送的延迟则会导致订单的流失。

发生这种情况的可能性就代表了一种风险。

当使用电子表格模型时,分析家习惯将那些本来不确定的变量用其平均值或其最佳估计值来输入。

这是因为电子表格软件只允许他们在一个单元格内输入一个数值或一个公式。

这些确定的模型只能产生一个结果。

而模型结果将被用作商业或技术决策的根据。

为了把握模型中本身存在的那些不确定性,分析家只能通过手工方式来改变模型变量,分析它们对关键结果的影响,来简单地实现方案分析。

这种方法提供了可能结果的一定范围,但它无法使人得知那些特定结果出现的可能性。

管理者经常需要知道那些不确定变量分别取什么值的时候,方案会达到一个最佳情况;或在什么时候,方案会达到一个最差情况;又在什么时候,方案又会达到一个最可能情况。

Crystal Ball 项目风险分析评估工具

Crystal Ball 项目风险分析评估工具
CD-ROM drive
Video graphics adapter and monitor with at least 1024x768 resolution
Adobe Acrobat Reader 6.0 or later
Note: For Real Options Analysis Toolkit, Windows and Excel must be English versions and the Windows regional settings must be English.
Personal computer with Pentium-equivalent microprocessor (800 MHz or faster)
At least 512 MB of RAM
At least 88 MB of hard disk space for .NET Framework 2.0 and another 58 MB for .NET Framework 3.0 (if not already installed) and 91 MB for Crystal Ball 7.3.1. (Note: Each of those two components requires approximately twice the given amount of disk space during installation.)
Crystal Ball 7 Standard Edition is the easiest way to perform Monte Carlo simulations in your own spreadsheets. Crystal Ball automatically calculates thousands of different "what if" cases, saving the inputs and results of each calculation as individual scenarios. Analysis of these scenarios reveals to you the range of possible outcomes, their probability of occurring, which input has the most effect on your model and where you should focus your efforts.

CrystalBall风险分析蒙特卡洛模拟分析软件

CrystalBall风险分析蒙特卡洛模拟分析软件

CrystalBall风险分析蒙特卡洛模拟分析软件转换Microsoft Excel电⼦表格,获得可信的风险分析图,创建准确的预测模型,寻找最佳解决⽅案,最⼤限度的提⾼您所⾯临的风险。

Crystal Ball软件提供从蒙特卡洛模拟到预测和优化的功能。

Crystal Ball是⽯油、天然⽓和矿业公司分析电⼦表格模型中不确定性的⾏业标准软件。

Crystal Ball是在⾃⼰的电⼦表格中进⾏快速风险分析和优化的最简单⽅法。

使⽤⼀个集成的⼯具集,您可以使⽤您⾃⼰的历史数据来建⽴精确的模型,⾃动“what if”分析来理解潜在的不确定性的影响,并寻找最佳的解决⽅案或项⽬组合。

Oracle Crystal Ball是⽤于预测建模、预测、模拟和优化的,基于电⼦表格的主要应⽤程序。

它使您对影响风险的关键因素有⽆与伦⽐的洞察⼒。

使⽤Crystal Ball,即使在最不确定的市场条件下,您也能做出正确的战术决策以达到您的⽬标并获得竞争优势。

新功能⽀持Microsoft Excel 2016⽀持Microsoft Windows 10改进了预测功能Cell偏好功能增强附加语⾔本地化OptQues优化功能增强预测Damped趋势指数平滑技术Crystal Ball EPM整合战略财务Crystal Ball决策优化器与战略财务的整合选择分类对象基本功能增加风险计算的概率达到某⼀⽬标的可能性是什么?影响风险的关键因素是什么?对这些和其他常见的“what-if”⽅案的回答可以通过将概率分配给未知变量来确定。

Excel⽆法处理概率分析的复杂性,因此需要更好的⼯具—Crystal Ball。

Crystal Ball通过对每个不确定变量应⽤⼀系列的值或概率分布,使⽤蒙特卡洛模拟的繁琐的“what-if”过程⾃动化。

程序从定义的概率范围内⽣成随机值,然后重新计算模型成百上千次,保存每个“what-if”场景的结果。

这个节省时间的缓解⽅法,必须⼀次⼜⼀次⼿动输⼊不同的场景。

crystal ball使用指导

crystal ball使用指导

crystal ball使用指导Crystal Ball使用指导Crystal Ball是一种常用的预测和决策支持工具,它基于蒙特卡洛仿真技术,可以对不确定性进行建模和分析。

下面将介绍一些使用Crystal Ball的指导,帮助您更好地利用这一工具进行预测和决策。

一、数据准备在使用Crystal Ball之前,首先要准备好相应的数据。

这些数据可以是历史数据、统计数据或者是专家意见。

确保数据的准确性和完整性非常重要,因为这些数据将直接影响到Crystal Ball的分析结果。

二、建立模型在Crystal Ball中,模型是指对问题进行描述和建模的过程。

模型的建立需要根据具体问题的特点来确定。

首先需要确定决策变量和随机变量,然后建立它们之间的关系。

在建立模型时,要保证模型的可靠性和合理性。

三、运行仿真在完成模型建立后,就可以进行仿真运行了。

Crystal Ball使用蒙特卡洛仿真技术,通过随机抽样来模拟不同可能的情况。

这样可以得到一系列可能的结果,并对其进行统计分析。

四、分析结果Crystal Ball提供了多种统计分析方法,可以帮助用户对仿真结果进行分析和解释。

常用的分析方法包括概率分布分析、敏感性分析和决策树分析等。

通过这些分析,可以得到关键决策变量的概率分布、敏感性程度以及最优决策方案等信息。

五、结果解释和应用在分析结果之后,需要对结果进行解释和应用。

Crystal Ball提供了可视化工具,可以将分析结果以图表的形式展示出来,帮助用户更好地理解和应用结果。

同时,还可以通过对结果的解释和讨论,对决策方案进行优化和调整。

六、风险管理Crystal Ball除了用于预测和决策支持,还可以用于风险管理。

通过对不确定性的建模和分析,可以帮助用户识别和评估潜在的风险,并采取相应的措施进行风险管理和控制。

七、案例分析以下是一个使用Crystal Ball进行预测和决策的案例分析。

假设某公司要决定是否投资于某个新项目。

风险管理软件Crystal-Ball使用指导

风险管理软件Crystal-Ball使用指导

Monte-Carlo Simulation with Crystal Ball®To run a simulation using Crystal Ball®:1. Setup SpreadsheetBuild a spreadsheet that will calculate the performance measure (e.g., profit) in terms of the inputs (random or not). For random inputs, just enter any number.2. Define Assumptions—i.e., random variablesDefine which cells are random, and what distribution they should follow.3. Define Forecast—i.e., output or performance measureDefine which cell(s) you are interested in forecasting (typically the performance measure, e.g., profit).4. Choose Number of TrialsSelect the number of trials. If you would later like to generate the Sensitivity Analysis chart, choose “Sensitivity Analysis” under Options in Run Preferences.5. Run SimulationRun the simulation. If you would like to change parameters and re-run the simulation, you should “reset” the simulation (click on the “Reset Simulation” button on the toolbar or in the Run menu) first.6. View ResultsThe forecast window showing the results of the simulation appears automatically after (or during) the simulation. Many different results are available (frequency chart, cumulative chart, statistics, percentiles, sensitivity analysis, and trend chart). The results can be copied into the worksheet.Crystal Ball Toolbar:Define Define Run Start Reset Forecast Trend Assumptions Forecast Preferences Simulation Simulation Window ChartWalton Bookstore Simulation with Crystal Ball®Recall the Walton Bookstore example: It is August, and they must decide how many of next year’s nature calendars to order. Each calendar costs the bookstore $7.50 and is sold for $10. After February, all unsold calendars are returned to the publisher for a refund of $2.50 per calendar. Suppose Walton predicts demand will be somewhere between 100 and 300 (discrete uniform).Demand = d ~ Uniform[100, 300]Order Quantity = Q (decision variable)Revenue = $10 * Min(Q, d)Cost = $7.50 * QRefund = $2.50 * Max(Q–d, 0)Profit = Revenue – Cost + RefundStep #1 (Setup Spreadsheet)Walton Bookstore Simulation with Crystal Ball ®Step #2 (Define Assumptions —i.e., random variables)—color code (blue):and click on the “Define Assumptions” button in toolbar (or in the Cell menu):Select type of distribution:Provide parameters of distributions:Walton Bookstore Simulation with Crystal Ball®Step #3 (Define Forecast—i.e., output)click on the “Define Forecast” button in toolbar (or in the Cell menu),and fill in the Define Forecast dialogue box.Step #4 (Choose Number of Trials)Click on the “Run Preferences” button in toolbar (or in the Run menu):and select the number of trials to run.Walton Bookstore Simulation with Crystal Ball®Step #5 (Run Simulation)Click on the “Start Simulation” button in toolbar (or Run in the Run menu):Step #6 (View Results)The results of the simulation can be viewed in a variety of different ways (frequency chart, cumulative chart, statistics, and percentiles). Choose different options under the View menuin the forecast window.The results can be copied into a worksheet or Word document (choose Copy under the Edit menu in the simulation output window.Using Trend Charts to Find the Impact of Order Quantityon Potential ProfitDefine several forecast cells (G14:G18) for several possible order quantities (Q=100, 150, 200, 250, 300). Use the same random order quantity for each to compare them more equally (i.e., one assumption cell for demand—C14—with the rest set equal to C14).After running the simulation, choose “Open Trend Chart” in the Run menu. This chart gives “certainty bands” for the forecast cells. 10% of the time, the project duration will fall within the inner band (light blue), 25% of the time within the 2nd band (red), 50% of the time within the third band (green), and 90% of the time within the outside band (dark blue).Project Management—Global OilGlobal Oil is planning to move their credit card operation to Des Moines, Iowa from their home office in Dallas. The move involves many different divisions within the company. Real estate must select one of three available office sites. Personnel has to determine which employees from Dallas will move, how many new employees to hire, and who will train them. The systems group and treasurer’s office must organize the new operating procedure and make financial arrangements. The architects will have to design the interior space, and oversee needed structural improvements. Each site is an existing building with sufficient open space, but office partitions, computer facilities, furnishings, and so on, must all be provided.A complicating factor is that there is an interdependence of activities. In other words, some parts of the project cannot be started until other parts are completed. For example, Global cannot construct the interior of an office before it has been designed. Neither can it hire new employees until it has determined its personnel requirements.The necessary activities and their necessary predecessors (due to interdependence) are listed below. Three estimates are made for the completion time of each activity—the minimum time, most likely time, and maximum time.Start EndGlobal Oil Simulation with Crystal Ball®Step #1 (Setup Spreadsheet)Step #2 (Define Assumptions—i.e., random variables)Each of the random activity times (B, C, D, E, G, and I) is assumed to follow the triangular distribution.Global Oil Simulation with Crystal Ball®Step #3 (Define Forecast—i.e., output)Cell J15 is the forecast cell:Step #4 (Choose Number of Trials)500 trials were run. In addition, Sensitivity Analysis was enabled in the Options of the Run Preferences dialogue box. This allows for the generation of sensitivity analysis results later.Step #5 (Run Simulation)Step #6 (View Results)Additional Results Available with Crystal Ball®Slide the triangles below the histograms to determine the probability that the output (project duration) is less than a certain value (e.g., a deadline), greater than a certain value, or between any two values (by sliding both triangles).Alternatively, you can type in values for the lower bound or upper bound to determine the probability. You can also type in a probability (in “Certainty”), and it will determine the range that has that probability.There is a 79% chance the project will be completed within 150 days.There is a 2.4% chance that the project will take more than 160 days.Sensitivity ChartChoose “Open Sensitivity Chart” in the R un menu. Note that this chart is only available ifyou selected the “Sensitivity Analysis” option under Run Preferences. This chart gives an indication as to which random variables (activity times) have the greatest impact on the output cell (project completion time).Variability in activity E has the greatest impact on overall project duration, followed by activity D, C, I, and B. Variability in activity G has almost no impact.Fitting a DistributionCrystal Ball can be used to “fit” a distribution t o data.The following data has been collected for the previous 100 phone calls to a mail-order house:(80 rows have been hidden)Fitting Data to a DistributionUsing Crystal Ball® to fit data to a distribution1. Select a spreadsheet cell.2. Choose Define Assumption.3. Click the Fit button, then select the source of the fitted data.4. Click the Next button, then select the distributions to try to fit.5. Click OK.Interarrival TimeService Time。

风险管理软件Cryst精编B精编l使用指导

风险管理软件Cryst精编B精编l使用指导

风险管理软件C r y s t精编B精编l使用指导 Document number:BGCG-0857-BTDO-0089-2022Monte-Carlo Simulation with Crystal Ball?To run a simulation using Crystal Ball?:1. Setup SpreadsheetBuild a spreadsheet that will calculate the performance measure ., profit) in terms of the inputs (random or not). For random inputs, just enter any number.2. Define Assumptions—., random variablesDefine which cells are random, and what distribution they should follow.3. Define Forecast—., output or performance measureDefine which cell(s) you are interested in forecasting (typically the performance measure, ., profit).4. Choose Number of TrialsSelect the number of trials. If you would later like to generate the Sensitivity Analysis chart, choose “Sensitivity Analysis” under Options in Run Preferences.5. Run SimulationRun the simulation. If you would like to change parameters and re-run the simulation, you should “reset” the simulation (click on the “Reset Simulation” button on the toolbar or in the Run menu) first.6. View ResultsThe forecast window showing the results of the simulation appears automatically after (or during) the simulation. Many different results are available (frequency chart, cumulative chart, statistics, percentiles, sensitivity analysis, and trend chart). The results can be copied into the worksheet.Crystal Ball Toolbar:Define Define Run Start Reset Forecast Trend Assumptions Forecast Preferences S imulation Simulation Window ChartWalton Bookstore Simulation with Crystal Ball?Recall the Walton Bookstore example: It is August, and they must decide how many of next year’s nature calendars to order. Each calendar costs the bookstore $ and is sold for $10. After February, all unsold calendars are returned to the publisher for a refund of $ per calendar. Suppose Walton predicts demand will be somewhere between 100 and 300 (discrete uniform).Demand = d ~ Uniform[100, 300]Order Quantity = Q (decision variable)Revenue = $10 * Min(Q, d)Cost = $ * QRefund = $ * Max(Q–d, 0)Profit = Revenue – Cost + RefundStep #1 (Setup Spreadsheet)Walton Bookstore Simulation with Crystal Ball ?Step #2 (Define Assumptions —., random variables)Select the cell that contains the random variable (B17) — color codeand click on the “Define Assumptions” button in toolbar (or in the Cell menu):Select type of distribution:Provide parameters of distributions:Walton Bookstore Simulation with Crystal Ball?Step #3 (Define Forecast—., output)click on the “Define Forecast” button in toolbar (or in the Cell menu),and fill in the Define Forecast dialogue box.Step #4 (Choose Number of Trials)Click on the “Run Preferences” button in toolbar (or in the Run menu):and select the number of trials to run.Walton Bookstore Simulation with Crystal Ball?Step #5 (Run Simulation)Click on the “Start Simulation” button in toolbar (or Run in the Run menu):Step #6 (View Results)The results of the simulation can be viewed in a variety of different ways (frequency chart, cumulative chart, statistics, and percentiles). Choose different options under the View menu in the forecast window.The results can be copied into a worksheet or Word document (choose Copy under the Edit menu in the simulation output window.Using Trend Charts to Find the Impact of Order Quantity on PotentialProfitDefine several forecast cells (G14:G18) for several possible order quantities (Q=100, 150, 200, 250, 300). Use the same random order quantity for each to compare them more equally ., one assumption cell for demand—C14—with the rest set equal to C14).After running the simulation, choose “Open Trend Chart” in the Run menu. This chart gives “certainty bands” for the forecast cells. 10%of the time, the project duration will fall within the inner band (light blue), 25% of the time within the 2nd band (red), 50% of the time within the third band (green), and 90% of the time within the outside band(dark blue).Project Management—Global OilGlobal Oil is planning to move their credit card operation to Des Moines, Iowa from their home office in Dallas. The move involves many different divisions within the company. Real estate must select one of three available office sites. Personnel has to determine which employees from Dallas will move, how many new employees to hire, and who will train them. The system s group and treasurer’s office must organize the new operating procedure and make financial arrangements. The architects will have to design the interior space, and oversee needed structural improvements. Each site is an existing building with sufficient open space, but office partitions, computer facilities, furnishings, and so on, must all be provided.A complicating factor is that there is an interdependence of activities. In other words, some parts of the project cannot be started until other parts are completed. For example, Global cannot construct the interiorof an office before it has been designed. Neither can it hire new employees until it has determined its personnel requirements.The necessary activities and their necessary predecessors (due to interdependence) are listed below. Three estimates are made for the completion time of each activity—the minimum time, most likely time,and maximum time.Start EndGlobal Oil Simulation with Crystal Ball? Step #1 (Setup Spreadsheet)Step #2 (Define Assumptions—., random variables)Each of the random activity times (B, C, D, E, G, and I) is assumed to follow the triangular distribution.Global Oil Simulation with Crystal Ball?Step #3 (Define Forecast—., output)Cell J15 is the forecast cell:Step #4 (Choose Number of Trials)500 trials were run. In addition, Sensitivity Analysis was enabled in the Options of the Run Preferences dialogue box. This allows for the generation of sensitivity analysis results later.Step #5 (Run Simulation)Step #6 (View Results)Additional Results Available with Crystal Ball?Slide the triangles below the histograms to determine the probability that the output (project duration) is less than a certain value ., a deadline), greater than a certain value, or between any two values (by sliding both triangles).Alternatively, you can type in values for the lower bound or upper bound to determine the probability. You can also type in a probability (in “Certainty”), and it will determine the range that has that probability.There is a 79% chance the project will be completed within 150 days. There is a % chance that the project will take more than 160 days.Sensitivity ChartChoose “Open Sensitivity Chart” in the Run menu. Note that this chartis only available if you selected the “Sensitivity Analysis” optionunder Run Preferences. This chart gives an indication as to which random variables (activity times) have the greatest impact on the output cell (project completion time).Variability in activity E has the greatest impact on overall project duration, followed by activity D, C, I, and B. Variability in activity G has almost noimpact.Fitting a DistributionCrystal Ball can be used to “fit” a distribution to data.The following data has been collected for the previous 100 phone calls to a mail-order house:(80 rows have been hidden)Fitting Data to a DistributionUsing Crystal Ball? to fit data to a distribution1. Select a spreadsheet cell.2. Choose Define Assumption.3. Click the Fit button, then select the source of the fitted data.4. Click the Next button, then select the distributions to try to fit.5. Click OK.Interarrival TimeService Time。

crystalball模拟基础教程

crystalball模拟基础教程

➢ 运输业收入管理(13.6节)
13.43–13.48
➢ 选择合适的分配(13.7节)
13.49–13.68
➢ 利用决策表做决策(13.8节)
13.69–13.84
第1页/共© T8h5e页McGraw-Hill Companies, Inc., 2009
13-2
学习目标
➢ 在读完本章后,你应该能够:
13-33
现金流量管理:沼泽地黄金岁月公司
➢ 面对了暂时性的业绩下滑以及一些现在和未来的建造 成本,所以公司在未来几年内将面临负现金流量。
➢ 财经日报的销售资料:
– 佛莱迪每天的销售量介于40到70份之间。 – 销售数量介于40到70份之间任何数值的频率相同。
第3页/共© T8h5e页McGraw-Hill Companies, Inc., 2009
13-4
运用仿真之电子表格模式
第4页/共© T8h5e页McGraw-Hill Companies, Inc., 2009
13-22
竞争者 2 之三角分配
第22页/©共T8he5M页cGraw-Hill Companies, Inc., 2009
13-23
信用公司竞标问题的结果
第23页/©共T8he5M页cGraw-Hill Companies, Inc., 2009
13-24
信用公司竞标问题的结果(续)
第24页/©共T8he5M页cGraw-Hill Companies, Inc., 2009
第6页/共© T8h5e页McGraw-Hill Companies, Inc., 2009
13-7
Crystal Ball 分配图库
第7页/共© T8h5e页McGraw-Hill Companies, Inc., 2009

Crystal_Ball_蒙塔卡洛模拟教程

Crystal_Ball_蒙塔卡洛模拟教程

13-4
報童佛萊迪
➢ 佛莱迪在某大城市里主要市区经营一家报摊。
➢ 佛莱迪贩售各类的报纸和杂志,其中最贵的报纸为财经日报 。 ➢ 财经日报相关的成本资料: 每份报纸的成本为1.50美元 每份报纸的售价为2.50美元 没售出的报纸,每份报纸可以获得0.50美元的偿还金 ➢ 财经日报的销售资料: 佛莱迪每天的销售量介于40到70份之间。 销售数量介于40到70份之间任何数值的频率相同。
© The McGraw-Hill Companies, Inc., 2009
13-19
准确度控制:扩充的定义预测对话方块
© The McGraw-Hill Companies, Inc., 2009
13-20
準確度控制的結果
1,000 次試驗得出有95%信賴區間低於1美元。
© The McGraw-Hill Companies, Inc., 2009
© The McGraw-Hill Companies, Inc., 2009
13-15
佛萊迪利潤的頻率圖
© The McGraw-Hill Companies, Inc., 2009
13-16
佛萊迪利潤更多的結果
© The McGraw-Hill Companies, Inc., 2009
Certainty 栏位显示佛萊迪的模拟实验中
– 竞争者 2 则设定 25% 的边际利润以及他在估算计画成本时会比 竞争者 1 来得准确;但是根据过去的竞标经验,他的边际利润也 有可能在至多正负15% 间移动。
– 竞争者 3 估算计画成本极为精准,将其边际利润设在介于 20% 与30% 之间的任一数字。
問題:信用公司對於這個計畫的投資金額應該是多少?

水晶球软件使用Crystal Ball

水晶球软件使用Crystal Ball
• This is in contrast to analytical methods, which obtain exact solutions to highly stylized problems
• Tradeoff between rigor and relevance
精选可编辑ppt
OPIM 5270 |Spring 2015
• Alternatives with the same expected value may involve very different levels of risk.
精选可编辑ppt
OPIM 5270 |Spring 2015
Methods of Risk Analysis
• Best-Case/Worst-Case Analysis • What-if Analysis • Simulation
精选可编辑ppt
OPIM 5270 |Spring 2015
Monte Carlo Simulation
• Monte Carlo simulation is a method by which approximate solutions are obtained to realistic (and therefore complicated) problems
Project Management Session 9 Crystal Ball
OPIM 5270
精选可编辑ppt
OPIM 5270 |Spring 2015
Session 9 Goals
Understand why risk must be analyzed Know pros / cons for three ways to analyze risk Identify random variables in models Know the four steps of a simulation process Generate random numbers with Crystal Ball Use the four steps of a simulation process Explain how Crystal Ball supports Proj. Mgmt.

crystal ball软件介绍

crystal ball软件介绍

Crystal Ball 介绍Crystal Ball(CB)是基于PC Windows平台而开发的简单且非常实用的风险分析和评估软件。

面向各类商务、科学和技术工程领域,用户界面友好,是基于图表进行预测和风险分析。

CB 在微软Excel 应用软件上运行,使用蒙特卡罗(Monte Carlo)模拟法对某个特定状况预测所有可能的结果,运用图表对分析进行总结,并显示每一个结果的概率。

除了描述统计量、趋势图和相关变量分配,CB还进行敏感性分析,让用户决定真正导致结果的因素。

如今 CB 已是全世界商业风险分析和决策评估软件中的佼佼者。

Crystal Ball专业版是市面上以Excel为本的风险分析及预测工具中最全面的套装软件。

其功能和特点不仅早已得到广大用户的认同,并获得许多正在考虑购买相关软件产品新用户的青睐和首选。

85%<<财富>>评出的全球500强大企业中早已有400家使用 Crystal Ball 软件作为他们进行商务决策,项目投资风险分析的工具。

再者,美国前50名最佳MBA 商学院,已有40所也用Crystal Ball作为教研和商业性课题的工具。

用户之一世界著名的哈佛大学商学院把 Crystal Ball 列为可用于计划金融的软件 (Project Finance Software)。

因为财政计划,金融投资方面的风险分析是CB 软件功能的一部分。

Crystal Ball之前是美国Decisioneering公司的产品,Decisioneering在2007年被Hyperion公司收购,Hyperion 公司之后又被Oracle收购,所以Crystal Ball目前的发行商是Oracle。

Crystal Ball的用途:DFSS,过程研究,过程优化,现有过程的模拟改变,公差分析,设计分析,原料筛选,容量设计,资源分配与存货优化,约束后的项目筛选,预防性维护优化,成本预算,可靠性分析,排队过程分析,建筑项目资金预算的偶然性分析,商业过程模拟,工程设计与预测,供求预测,制造供应链问题的减少与存货控制,新产品商品化的资金模型。

crystal-ball-模拟基础教程.ppt

crystal-ball-模拟基础教程.ppt

13-11
Crys设定执行偏好
➢ 设定执行偏好就是要决定执行试验的次数,并且决定如 何执行计算机仿真的其他选项。
➢ 一开始,我们点选「Crystal Ball」标签(Excel 2007)或 是工具栏(Excel较早版本)上的「Run Preferences」 (执行偏好)按钮。
– 对于每项工作,估计其完成时间皆以用三种时间—最可能、最 乐观、以及最悲观的估计量。
问题:项目将于期限内完成的机率为何?
13-27
信用建设公司的项目网络图
13-28
每项活动时间的三角分配
13-29
运用计算机仿真之电子表格模式
13-30
三角分配的对话框
13-31
信用公司项目期间的结果
13-32
13-4
报童佛莱迪
➢ 佛莱迪在某大城市里主要市区经营一家报摊。
➢ 佛莱迪贩卖各类的报纸和杂志,其中最贵的报纸为财 经日报 。
➢ 财经日报相关的成本资料:
– 每份报纸的成本为1.50美元 – 每份报纸的售价为2.50美元 – 没售出的报纸,每份报纸可以获得0.50美元的偿还金
➢ 财经日报的销售资料:
乘其他公司飞往芝加哥的班机。而这样做的总成本为450美元(包 括:重订其他班机、机票抵用券及商誉损失等)。
问题:环球航空公司对于此航班应该接受多少的订位?
13-45
运用计算机仿真之电子表格模式
13-46
现身搭机人数之二项分配
13-47
利润之频率图
13-48
乘坐机位数之频率图
13-49
无法登机人数之频率图
➢ 最可能值落在某数值(平均值) ➢ 接近平均值的数值发生机率较高 ➢ 对称(平均值上下方图形相似) ➢ 极值可能会发生,但是非常罕见

风险管理软件CrystalBall操作指南(英文版)(doc 16页)

风险管理软件CrystalBall操作指南(英文版)(doc 16页)

风险管理软件CrystalBall操作指南(英文版)(doc 16页)Monte-Carlo Simulation with Crystal Ball®To run a simulation using Crystal Ball®:1. Setup SpreadsheetBuild a spreadsheet that will calculate the performance measure (e.g., profit) in terms of the inputs (random or not). For random inputs, just enter any number.2. Define Assumptions—i.e., random variablesDefine which cells are random, and what distribution they should follow.3. Define Forecast—i.e., output or performance measureDefine which cell(s) you are interested in forecasting (typically the performance measure, e.g., profit).4. Choose Number of TrialsSelect the number of trials. If you would later like to generate the Sensitivity Analysis chart, choose “Sensitivity Analysis” under Options in Run Preferences.5. Run SimulationRun the simulation. If you would like to change parameters and re-run the simulation, you should “reset” the simulation (click on the “Reset Simulation” button on the toolbar or in the Run menu) first.Walton Bookstore Simulation with Crystal Ball®Recall the Walton Bookstore example: It is August, and they must decide how many of next year’s nature calendars to order. Each calendar costs the bookstore $7.50 and is sold for $10. After February, all unsold calendars are returned to the publisher for a refund of $2.50 per calendar. Suppose Walton predicts demand will be somewhere between 100 and 300 (discrete uniform).Demand = d ~ Uniform[100, 300]Order Quantity = Q (decision variable)Revenue = $10 * Min(Q, d)Cost = $7.50 * QRefund = $2.50 * Max(Q–d, 0)Profit = Revenue – Cost + RefundStep #1 (Setup Spreadsheet)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17A B C D E F Simulation of Walton's BookstoreD ataU ni t C ost =$7.50U ni t P rice =$10.00U ni t R ef und =$2.50D emand D is tribution (Uniform)M inim um =100M axi mum =300D ecis ion VariableOrder Quantity =200SimulationD em and R evenue C ost R efund P rof i t200$2,000.00$1,500.00$0.00$500.0015 16 17B C D E F SimulationD em and R evenue C ost R efund P rofi t 200=C5*M IN(C13,B17)=C4*C13=C6*M A X(C13-B17,0)=C17-D17+E17Walton Bookstore Simulation with Crystal Ball ®Step #2 (Define Assumptions —i.e., random variables)—color code (blue):1617B D emand 200and click on the “Define Assumptions” button in toolbar (or in the Cell menu):Select type of distribution:Provide parameters of distributions:8910B CD emand Distribution (U niform)M inim um =100M axi mum =300Walton Bookstore Simulation with Crystal Ball ®Step #3 (Define Forecast —i.e., output)1617F P rof i t$500.00click on the “Define Forecast” button in toolbar (or in the Cell menu),and fill in the Define Forecast dialogue box.Step #4 (Choose Number of Trials)Click on the “Run Preferences” button in toolbar (or in the Run menu):and select the number of trials to run.Walton Bookstore Simulation with Crystal Ball ®Step #5 (Run Simulation)Click on the “Start Simulation” button in toolbar (or Run in the Run menu):Step #6 (View Results)The results of the simulation can be viewed in a variety of different ways (frequency chart, cumulative chart, statistics, and percentiles). Choose different options under the View menu in the forecast window.The results can be copied into a worksheet or Word document (choose Copy under the Edit menu in the simulation output window.Using Trend Charts to Find the Impact of Order Quantityon Potential ProfitDefine several forecast cells (G14:G18) for several possible order quantities (Q=100, 150, 200, 250, 300). Use the same random order quantity for each to compare them more equally (i.e., one assumption cell for demand—C14—with the rest set equal to C14).1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18A B C D E F G Simulation of Walton's BookstoreD ataU ni t C ost =$7.50U ni t P rice =$10.00U ni t R ef und =$2.50D emand D is tribution (Uniform)M inim um =100M axim um =300SimulationOrder Quantity D em and R evenue C ost R efund P rof it 100200$1,000.00$750.00$0.00$250.00150200$1,500.00$1,125.00$0.00$375.00200200$2,000.00$1,500.00$0.00$500.00250200$2,000.00$1,875.00$125.00$250.00300200$2,000.00$2,250.00$250.00$0.0012 13 14 15 16 17 18B C D E F G SimulationOrder Quantity D em and R evenue C ost R efund P rofi t 100200=$C$5*M IN(B14,C14)=$C$4*B14=$C$6*M AX(B14-C14,0)=D14-E14+F14 150=$C$14=$C$5*M IN(B15,C15)=$C$4*B15=$C$6*M AX(B15-C15,0)=D15-E15+F15 200=$C$14=$C$5*M IN(B16,C16)=$C$4*B16=$C$6*M AX(B16-C16,0)=D16-E16+F16 250=$C$14=$C$5*M IN(B17,C17)=$C$4*B17=$C$6*M AX(B17-C17,0)=D17-E17+F17 300=$C$14=$C$5*M IN(B18,C18)=$C$4*B18=$C$6*M AX(B18-C18,0)=D18-E18+F18After running the simulation, choose “Open Trend Chart” in the Run menu. This chart gives “certainty bands” for the forecast cells. 10% of the time, the project duration will fall within the inner band (light blue), 25% of the time within the 2nd band (red), 50% of the time within the third band (green), and 90% of the time within the outside band (dark blue).Project Management—Global OilGlobal Oil is planning to move their credit card operation to Des Moines, Iowa from their home office in Dallas. The move involves many different divisions within the company. Real estate must select one of three available office sites. Personnel has to determine which employees from Dallas will move, how many new employees to hire, and who will train them. The systems group and treasurer’s office must organize the new operating procedure and make financial arrangements. The architects will have to design the interior space, and oversee needed structural improvements. Each site is an existing building with sufficient open space, but office partitions, computer facilities, furnishings, and so on, must all be provided.A complicating factor is that there is an interdependence of activities. In other words, some parts of the project cannot be started until other parts are completed. For example, Global cannot construct the interior of an office before it has been designed. Neither can it hire new employees until it has determined its personnel requirements.The necessary activities and their necessary predecessors (due to interdependence) are listed below. Three estimates are made for the completion time of each activity—the minimum time, most likely time, and maximum time.Immediate Time Estimates (days)Minimum Most Likely Maximum Activity Description PredecessorA Select Office Site —21 21 21B Create Org. & Fin. Plan —20 25 30C Determine Personnel Req. B 15 20 30D Design Facility A, C 20 28 42E Construct Facility D 40 48 66F Select Personnel to Move C 12 12 12G Hire New Employees F 20 25 32H Move Key Employees F 28 28 28 I Train New PersonnelE, G, H1015 24ABCDFGHIEStartEndGlobal Oil Simulation with Crystal Ball®Step #1 (Setup Spreadsheet)1 2 3 4 5 6 7 8 9 10 11 12 13 14 15A B C D E F G H I J Global Oil Relocation ProjectActivity Tim e (Triangular)Im m edi ate M ost Start Activity Finish Activity D escri ption P redecessors M inim um Likely M axi mum Tim e Tim e Tim eA Sel ect Site-21212102121B C reate Org. & Fin. P lan-20253002525C D eterm ine P ersonnel Req.B152030252045D D esign Facil ity A, C202842452873E C onstruct Facility D4048667348121F Sel ect Personnel to M ove C121212451257G H ire New Em ployees F202532572582H M ove Key E mployees F282828572885I Train N ew P ersonnel E, G, H10152412115136P roject C om pleti on Tim e =136.003456789101112131415H I JStart Activity FinishTim e Tim e Tim e021=H5+I5025=H6+I6=J620=H7+I7=M A X(J5,J7)28=H8+I8=J848=H9+I9=J712=H10+I10=J1025=H11+I11=J1028=H12+I12=M A X(J9,J11,J12)15=H13+I13P roject C ompleti on Tim e ==J13Step #2 (Define Assumptions—i.e., random variables)Each of the random activity times (B, C, D, E, G, and I) is assumed to follow the triangular distribution.Global Oil Simulation with Crystal Ball®Step #3 (Define Forecast—i.e., output)Cell J15 is the forecast cell:15G H I J Project Completion Time =136.00Step #4 (Choose Number of Trials)500 trials were run. In addition, Sensitivity Analysis was enabled in the Options of the Run Preferences dialogue box. This allows for the generation of sensitivity analysis results later.Step #5 (Run Simulation)Step #6 (View Results)Additional Results Available with Crystal Ball®Slide the triangles below the histograms to determine the probability that the output (project duration) is less than a certain value (e.g., a deadline), greater than a certain value, or between any two values (by sliding both triangles).Alternatively, you can type in values for the lower bound or upper bound to determine the probability. You can also type in a probability (in “Certainty”), and it will determine the range that has that probability.There is a 79% chance the project will be completed within 150 days.There is a 2.4% chance that the project will take more than 160 days.Sensitivity ChartChoose “Open Sensitivity Chart” in the Run menu. Note that this chart is only availableif you selected the “Sensitivity Analysis” option under Run Preferences. This chartgives an indication as to which random variables (activity times) have the greatest impact on the output cell (project completion time).Variability in activity E has the greatest impact on overall project duration, followed by activity D, C, I, and B. Variability in activity G has almost no impact.Fitting a DistributionCrystal Ball can be used to “fit” a distribution to data.The following data has been collected for the previous 100 phone calls to a mail-order house:1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 99 100 101 102 103 104A B C D E F G H I Phone DataArrival Interarrival Length of Call Interarrival Length of Call Cus tomer #(minutes)Time(minutes)Time(minutes)18.228.22 3.77Averages 2.004 4.51212.25 4.03 4.53312.270.02 4.04416.26 3.98 3.70Simulation24518.06 1.81 5.38618.870.81 4.36723.46 4.58 4.41823.530.08 5.14928.73 5.20 4.761030.56 1.83 4.681132.36 1.80 5.061236.90 4.54 5.751343.30 6.40 4.061443.880.57 3.251545.17 1.29 3.5795194.020.28 4.2696195.48 1.46 3.3797195.870.38 4.4598196.840.98 5.0699197.810.97 5.20100200.43 2.61 4.25345G H IInterarrival Length of CallTime(minutes)Averages=AVERAGE(D5:D104)=AVERAGE(E5:E104)(80 rows have been hidden)Fitting Data to a DistributionUsing Crystal Ball® to fit data to a distribution1. Select a spreadsheet cell.2. Choose Define Assumption.3. Click the Fit button, then select the source of the fitted data.4. Click the Next button, then select the distributions to try to fit.5. Click OK.Interarrival TimeService Time。

crystal ball使用指导

crystal ball使用指导

crystal ball使用指导Crystal Ball使用指导导言:Crystal Ball是一款用于预测和分析风险的软件工具,它可以帮助企业和组织做出明智的决策。

本文将介绍如何使用Crystal Ball进行预测和分析,以及一些注意事项和技巧。

一、Crystal Ball简介Crystal Ball是由Oracle公司开发的一款风险分析软件,它基于蒙特卡罗模拟方法,可以通过模拟大量的随机变量来预测未来的风险和收益。

Crystal Ball可以用于各种决策问题,如项目管理、投资分析、供应链优化等,帮助用户做出更准确的决策。

二、Crystal Ball的使用步骤1. 数据输入:首先,我们需要将相关的数据输入到Crystal Ball 中。

可以直接在Crystal Ball中输入数据,也可以从外部文件导入数据。

在输入数据时,需要注意数据的格式和准确性。

2. 模型建立:在输入数据之后,我们需要建立相应的模型。

模型可以是简单的数学模型,也可以是复杂的模拟模型。

在建立模型时,需要考虑到各种变量之间的关系,并进行合理的假设和参数设定。

3. 分布设定:Crystal Ball中的随机变量需要设定相应的概率分布。

可以选择常见的分布,如正态分布、均匀分布等,也可以根据实际情况自定义分布。

在设定分布时,需要根据实际数据和经验进行合理的选择。

4. 模拟运行:一切准备就绪后,我们可以进行模拟运行。

Crystal Ball会根据设定的分布和模型进行大量的随机模拟,得到未来可能的结果。

可以设定模拟的次数,以增加结果的准确性。

5. 结果分析:模拟运行完成后,Crystal Ball会生成相应的结果。

我们可以通过查看统计指标、绘制图表等方式对结果进行分析。

可以计算平均值、方差、置信区间等,以评估风险和收益。

三、Crystal Ball的注意事项和技巧1. 数据准确性:Crystal Ball的结果取决于输入的数据,因此需要确保数据的准确性。

相关主题
  1. 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
  2. 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
  3. 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。

Monte-Carlo Simulation with Crystal Ball®To run a simulation using Crystal Ball®:1. Setup SpreadsheetBuild a spreadsheet that will calculate the performance measure (e.g., profit) in terms of the inputs (random or not). For random inputs, just enter any number.2. Define Assumptions—i.e., random variablesDefine which cells are random, and what distribution they should follow.3. Define Forecast—i.e., output or performance measureDefine which cell(s) you are interested in forecasting (typically the performance measure, e.g., profit).4. Choose Number of TrialsSelect the number of trials. If you would later like to generate the Sensitivity Analysis chart, choose “Sensitivity Analysis” under Options in Run Preferences.5. Run SimulationRun the simulation. If you would like to change parameters and re-run the simulation, you should “reset” the simulation (click on the “Reset Simulation” button on the toolbar or in the Run menu) first.6. View ResultsThe forecast window showing the results of the simulation appears automatically after (or during) the simulation. Many different results are available (frequency chart, cumulative chart, statistics, percentiles, sensitivity analysis, and trend chart). The results can be copied into the worksheet.Crystal Ball Toolbar:Define Define Run Start Reset Forecast Trend Assumptions Forecast Preferences Simulation Simulation Window ChartWalton Bookstore Simulation with Crystal Ball®Recall the Walton Bookstore example: It is August, and they must decide how many of next year’s nature calendars to order. Each calendar costs the bookstore $7.50 and is sold for $10. After February, all unsold calendars are returned to the publisher for a refund of $2.50 per calendar. Suppose Walton predicts demand will be somewhere between 100 and 300 (discrete uniform).Demand = d ~ Uniform[100, 300]Order Quantity = Q (decision variable)Revenue = $10 * Min(Q, d)Cost = $7.50 * QRefund = $2.50 * Max(Q–d, 0)Profit = Revenue – Cost + RefundStep #1 (Setup Spreadsheet)Walton Bookstore Simulation with Crystal Ball ®Step #2 (Define Assumptions —i.e., random variables)—color code (blue):and click on the “Define Assumptions” button in toolbar (or in the Cell menu):Select type of distribution:Provide parameters of distributions:Walton Bookstore Simulation with Crystal Ball®Step #3 (Define Forecast—i.e., output)click on the “Define Forecast” button in toolbar (or in the Cell menu),and fill in the Define Forecast dialogue box.Step #4 (Choose Number of Trials)Click on the “Run Preferences” button in toolbar (or in the Run menu):and select the number of trials to run.Walton Bookstore Simulation with Crystal Ball®Step #5 (Run Simulation)Click on the “Start Simulation” button in toolbar (or Run in the Run menu):Step #6 (View Results)The results of the simulation can be viewed in a variety of different ways (frequency chart, cumulative chart, statistics, and percentiles). Choose different options under the View menuin the forecast window.The results can be copied into a worksheet or Word document (choose Copy under the Edit menu in the simulation output window.Using Trend Charts to Find the Impact of Order Quantityon Potential ProfitDefine several forecast cells (G14:G18) for several possible order quantities (Q=100, 150, 200, 250, 300). Use the same random order quantity for each to compare them more equally (i.e., one assumption cell for demand—C14—with the rest set equal to C14).After running the simulation, choose “Open Trend Chart” in the Run menu. This chart gives “certainty bands” for the forecast cells. 10% of the time, the project duration will fall within the inner band (light blue), 25% of the time within the 2nd band (red), 50% of the time within the third band (green), and 90% of the time within the outside band (dark blue).Project Management—Global OilGlobal Oil is planning to move their credit card operation to Des Moines, Iowa from their home office in Dallas. The move involves many different divisions within the company. Real estate must select one of three available office sites. Personnel has to determine which employees from Dallas will move, how many new employees to hire, and who will train them. The systems group and treasurer’s office must organize the new operating procedure and make financial arrangements. The architects will have to design the interior space, and oversee needed structural improvements. Each site is an existing building with sufficient open space, but office partitions, computer facilities, furnishings, and so on, must all be provided.A complicating factor is that there is an interdependence of activities. In other words, some parts of the project cannot be started until other parts are completed. For example, Global cannot construct the interior of an office before it has been designed. Neither can it hire new employees until it has determined its personnel requirements.The necessary activities and their necessary predecessors (due to interdependence) are listed below. Three estimates are made for the completion time of each activity—the minimum time, most likely time, and maximum time.Start EndGlobal Oil Simulation with Crystal Ball®Step #1 (Setup Spreadsheet)Step #2 (Define Assumptions—i.e., random variables)Each of the random activity times (B, C, D, E, G, and I) is assumed to follow the triangular distribution.Global Oil Simulation with Crystal Ball®Step #3 (Define Forecast—i.e., output)Cell J15 is the forecast cell:Step #4 (Choose Number of Trials)500 trials were run. In addition, Sensitivity Analysis was enabled in the Options of the Run Preferences dialogue box. This allows for the generation of sensitivity analysis results later.Step #5 (Run Simulation)Step #6 (View Results)Additional Results Available with Crystal Ball®Slide the triangles below the histograms to determine the probability that the output (project duration) is less than a certain value (e.g., a deadline), greater than a certain value, or between any two values (by sliding both triangles).Alternatively, you can type in values for the lower bound or upper bound to determine the probability. You can also type in a probability (in “Certainty”), and it will determine the range that has that probability.There is a 79% chance the project will be completed within 150 days.There is a 2.4% chance that the project will take more than 160 days.Sensitivity ChartChoose “Open Sensitivity Chart” in the R un menu. Note that this chart is only available ifyou selected the “Sensitivity Analysis” option under Run Preferences. This chart gives an indication as to which random variables (activity times) have the greatest impact on the output cell (project completion time).Variability in activity E has the greatest impact on overall project duration, followed by activity D, C, I, and B. Variability in activity G has almost no impact.Fitting a DistributionCrystal Ball can be used to “fit” a distribution t o data.The following data has been collected for the previous 100 phone calls to a mail-order house:(80 rows have been hidden)Fitting Data to a DistributionUsing Crystal Ball® to fit data to a distribution1. Select a spreadsheet cell.2. Choose Define Assumption.3. Click the Fit button, then select the source of the fitted data.4. Click the Next button, then select the distributions to try to fit.5. Click OK.Interarrival TimeService Time。

相关文档
最新文档