All Discussions Tagged 'Simulation' - AnalyticBridge2020-05-31T23:31:16Zhttps://www.analyticbridge.datasciencecentral.com/forum/topic/listForTag?tag=Simulation&feed=yes&xn_auth=noThe Need for Speed: A performance comparison of Crystal Ball, ModelRisk, @RISK and Risk Solvertag:www.analyticbridge.datasciencecentral.com,2011-09-21:2004291:Topic:1519742011-09-21T18:58:16.286ZEric Torkiahttps://www.analyticbridge.datasciencecentral.com/profile/EricTorkia
<div class="discussion"><div class="description"><p><a href="http://storage.ning.com/topology/rest/1.0/file/get/2059716030?profile=original" target="_self"><img class="align-right" src="http://storage.ning.com/topology/rest/1.0/file/get/2059716030?profile=RESIZE_480x480" width="350"></img></a> There are very few performance comparisons available when considering the acquisition of an Excel-based Monte Carlo solution. It is with this in mind and a bit of intellectual curiosity that we decided to evaluate Oracle Crystal Ball, Palisade @Risk, Vose ModelRisk and Frontline Risk Solver in terms of speed, accuracy and…</p>
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<div class="discussion"><div class="description"><p><a target="_self" href="http://storage.ning.com/topology/rest/1.0/file/get/2059716030?profile=original"><img width="350" class="align-right" src="http://storage.ning.com/topology/rest/1.0/file/get/2059716030?profile=RESIZE_480x480" width="350"/></a>There are very few performance comparisons available when considering the acquisition of an Excel-based Monte Carlo solution. It is with this in mind and a bit of intellectual curiosity that we decided to evaluate Oracle Crystal Ball, Palisade @Risk, Vose ModelRisk and Frontline Risk Solver in terms of speed, accuracy and precision. We ran over 20 individual tests and 64 million trials to prepare comprehensive comparison of the top Monte-Carlo Tools.</p>
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<p>We have posted a full length PDF and the test results in Excel.</p>
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<p><a rel="nofollow" href="http://links.visibli.com/37a8e3becd332a23/?web=483803&dst=http%3A//www.crystalballservices.com/Resources/ConsultantsCornerBlog/EntryId/75/The-Need-for-Speed-A-performance-comparison-of-Crystal-Ball-ModelRisk-RISK-and-Risk-Solver.aspx" target="_blank">READ ARTICLE NOW</a></p>
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<p><a rel="nofollow" target="_blank" href="http://links.visibli.com/37a8e3becd332a23/?web=483803&dst=http%3A//www.crystalballservices.com/Resources/ConsultantsCornerBlog/EntryId/75/The-Need-for-Speed-A-performance-comparison-of-Crystal-Ball-ModelRisk-RISK-and-Risk-Solver.aspx">http://www.crystalballservices.com/Resources/ConsultantsCornerBlog/...</a></p>
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<p>I look forward to your comments and feedback!</p>
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<p>Eric</p>
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</div> Check out the 2nd part in the Excel Simulation Show-Down Video Series: Distribution Fitting (Risk Solver Vs. ModelRisk vs. Crystal Ball vs. "@risk")tag:www.analyticbridge.datasciencecentral.com,2011-05-18:2004291:Topic:1019662011-05-18T20:56:43.035ZEric Torkiahttps://www.analyticbridge.datasciencecentral.com/profile/EricTorkia
Just finished preparing the second installment in our video comparison of ModelRisk, Crystal Ball, Risk Solver and @Risk. <br></br> <br></br> This series compares distribution fitting capabilities of each package.<br></br> <br></br> This should prove interesting to the discussion. Please check it out and let me know what features we should look at next.…<br></br> <br></br>
Just finished preparing the second installment in our video comparison of ModelRisk, Crystal Ball, Risk Solver and @Risk. <br/> <br/> This series compares distribution fitting capabilities of each package.<br/> <br/> This should prove interesting to the discussion. Please check it out and let me know what features we should look at next.<br/> <br/> <a target="blank" href="http://www.linkedin.com/redirect?url=http%3A%2F%2Fwww%2Ecrystalballservices%2Ecom%2FResources%2FConsultantsCornerBlog%2FEntryId%2F72%2FExcel-Simulation-Show-Down-Part-2-Distribution-Fitting%2Easpx&urlhash=kd7Y&_t=tracking_anet" rel="nofollow">http://www.crystalballservices.com/Resources/ConsultantsCornerBlog/EntryId/72/Excel-Simulation-Show-Down-Part-2-Distribution-Fitting.aspx</a> To DOE or not to DOEtag:www.analyticbridge.datasciencecentral.com,2009-03-07:2004291:Topic:393392009-03-07T18:55:31.177ZJonathan Davishttps://www.analyticbridge.datasciencecentral.com/profile/JonathanDavis
I'm conducting a simulation analysis of how different system characteristics of a casualty evacuation aircraft (speed, capacity, range, number of aircraft) affect system performance (delays, timing through different levels of care etc). The purpose of the study is not to determine the optimal or near optimal set of characteristics, but to determine the marginal benefit or penalty of each aircraft system characteristic to the patient compared to the current system, so that if and when the system…
I'm conducting a simulation analysis of how different system characteristics of a casualty evacuation aircraft (speed, capacity, range, number of aircraft) affect system performance (delays, timing through different levels of care etc). The purpose of the study is not to determine the optimal or near optimal set of characteristics, but to determine the marginal benefit or penalty of each aircraft system characteristic to the patient compared to the current system, so that if and when the system is funded, designed and implemented, constraints such as cost, weight, volume can be evaluated within the context of patient outcomes, and the best *affordable* and *practical* design will be chosen based on benefit to patient outcome.<br />
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My question is whether anyone has recommendations for an experimental design to handle the following factor/levels:<br />
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A-2<br />
B-2<br />
C-4<br />
D-5<br />
E-5<br />
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All of these factors are significant and are the result of a sensitivity analysis starting with 12 factors. Factors C through E have so many levels because I'm not interested in just the extreme values, I'm interested the response each marginal change in factor levels has against a baseline. From previous experience with similar output, the response is highly nonlinear in factors C through E. Two factor interactions between C through E are significant. In places the response surface is not smooth or well behaved. The above experiment needs to be repeated 7 times under different sets of assumptions. To examine every permutation in all 7 cases requires 2800 runs each replicated 40 times, which translates to about 11 days of continuous computing on a single machine. I have a lab at my disposal and can run several machines, and I have the time to do it.<br />
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BUT. Do I need to? Given the nonlinear, poorly behaved nature of the response surface, does anyone have any recommendations as to how I can sample the decision space to adequately estimate the difference between any hypothetical system within the bounds of the experiment and the current capability (which is also simulated in a separate experiment)?<br />
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Thanks for any insights,<br />
Jon Calculus-level Programming for solving ODEs, PDEs, etc. Learn thru examples. Have math problem, need a solution?tag:www.analyticbridge.datasciencecentral.com,2008-11-07:2004291:Topic:282162008-11-07T17:06:25.142ZPhil B Brubakerhttps://www.analyticbridge.datasciencecentral.com/profile/PhilBBrubaker
(You) Have math problem, need a solution? If so and are willing to learn Calculus (level) Programming, then I'll help you write the code and use my (alpha) version of Fortran Calculus compiler to solve your problem. In exchange, you must tell at least 5 people about:<br></br>
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<div style="margin-left: 2em">o this AnalyticBridge website;<br></br> o Calculus-level Programming; and,<br></br> o Write-up your problem with Calculus Programming code as a <b>discussion</b> for others to learn from here on this…</div>
(You) Have math problem, need a solution? If so and are willing to learn Calculus (level) Programming, then I'll help you write the code and use my (alpha) version of Fortran Calculus compiler to solve your problem. In exchange, you must tell at least 5 people about:<br/>
<br />
<div style="margin-left: 2em">o this AnalyticBridge website;<br/> o Calculus-level Programming; and,<br/>
o Write-up your problem with Calculus Programming code as a <b>discussion</b> for others to learn from here on this website.</div>
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<div style="margin-left: 2em"><b>Major benefits</b> from Calculus Programming are: <br/> o Determines Optimal solution<br/> o Allows Rapid Model Prototyping<br/>
o Accelerates Problem "Understanding"<br/>
o Reduces Time & Costly Problem / Solution Cycle</div>
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<p>Tweaking 1000s of parameters at once is possible with Calculus programming. Math models can be algebraic, ODEs, PDEs, constrained, implicit, nonlinear, nested, etc. It solves them all with built in numerical methods. Leave the work to Calculus-level compilers. Users work on improving their math model and output displays (i.e. plots) and that's all. Nice and short. Try Calculus Programming, you'll love it!</p>
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<p>Visit <a href="http://www.digitalCalculus.com/example/intro.html" target="_blank">digitalCalculus.com examples</a> for industry problem write-ups.</p>
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<p>Thanks,<br/> Phil</p>