I need to respond to two classmate!

timer Asked: Sep 6th, 2018
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Discuss the difference between the Monte Carlo simulation and Crystal Ball. Under what conditions would you choose one over the other? Post an example to when each would be used. Be sure your example is different from the examples of your classmates.

Respond to at least two of your classmates. Discuss if you agree with their choice of under what conditions to use each type of simulation. Explain why you do or do not agree.

Refer to the Module Eight Discussion Rubric for directions on completing these discussions.

1 Running Head: Simulation methods Simulation Method Name of Student Institutional Affiliation Course Simulation Methods 2 Hello Class, Monte Carlo simulation is a mathematical technique that is computerized to allow people to account for risks based on quantitative analysis and decision making while the crystal ball is the spreadsheet-based application used in predictive modeling, optimization, forecasting, and simulation. Monte Carlo models the probability of different outcomes in a process that is quite difficult to be predicted as a result of the intervention of random variables. It also understands the impact of risk as well as the uncertainties in prediction and models used in forecasting. On the other hand, Crystal ball makes a provision of advanced optimization and calculation capabilities even though it does build on existing Monte Carlo and modeling tools for predictions. When it comes to choosing one simulation method over the other, there are a few conditions that should be measured. First, I would select Monte Carlo over Crystal ball because of it overs various benefits over deterministic/ single-point estimate analysis. Monet Carlo’s probabilistic results show what could happen and the nature of the outcome. It also creates graphs of various outcomes and their probabilities of occurrence. Additionally, it allows the modeling of interdependent relationships between input variables. Lastly, I would consider Monte Carlo because even Crystal ball used it in overcoming limitation experiences with traditional spreadsheet analysis. However, I would choose crystal ball over Monte Carlo because of a few factors. First, it provides several types of charts and reports that are displayed both graphically and numerically. Simulation Methods 3 Second, it is easy to extract the value of simulation when one wants to use them in other application. An instance where Monte Carlo simulation method can be used is when minimizing the energy of a system with the employment of Metropolis algorithm. One of the usages of the Metropolis algorithm is the Ising model. This involves choosing a pin, changing it and calculating the energy of the system that is if the energy minimizes accept it for calculation. This is repeated until the energy is minimized. Another instance where crystal ball is used is when a potential purchase wants to buy an apartment. The crystal ball will be used in making assumptions like the amount of rent to be paid in the area, the number of units to be rented per month, the operating costs per month for the entire apartment. These assumptions can be used in estimating the profitability of the apartment considering the various combinations of rented units and operating costs. References Charnes, J. (2013). Financial modeling with crystal ball and excel. Hoboken, NJ: Wiley. McLeish, D. L. (2013). Monte carlo simulation and finance. Hoboken, NJ: Wiley.
Week 8 Discussion Kanija Sayles posted Sep 5, 2018 1:39 PM Boiler tubes allow high pressure, high heat steam or water to flow through a boiler. Corrosion and oxidation can cause the tubes to crack or fail. Ideally, the tubes would be mended or replaced during a maintenance outage, but they can fail before then. Depending on the nature of the failure, the boiler may need to come offline in order to find and fix the faulty tubes, or it could be plugged until the outage. The company is Lean, and does not keep an excessive amount of parts in stock. A Monte Carlo simulation in Excel would help determine how many boiler tubes the maintenance department will need to purchase. A probability distribution would be set up to create a mathematical model for the failures, and random numbers would be allocated based on cumulative probability. The output would be the average failure rate and the average cost of replacement. This test would be replicated a few hundred times for optimal results. Excel’s built-in formulas would suffice for this relatively small amount of data (Balakrishnan, 2013). However, if maintenance decided to add on other pieces of equipment to get replaced during the outage, this would make the boiler tube spreadsheet cumbersome and messy. If the Maintenance Manager wanted to run several thousand trials, it could be done in Excel, but it would be tedious. These items are best addressed by using Oracle’s Crystal Ball add-in. Crystal Ball is designed to do simulations. It has built-in functions and procedures to easily replicate a test thousands of times. This is done by typing in the number of replications, as opposed to Excel where the user must physically select the areas to be populated. Crystal Ball does not show values in the replication cells, and Excel does. Excel’s Scenario Manager is similar to Crystal Ball’s Decision Table (Balakrishnan, 2013), (Oracle, 2018). My preference would be to use Crystal Ball simply because it is easy and convenient (though I have not used it nor the Monte Carlo simulation). I appreciate the fact that I am learning how to do simulations both ways. I think that putting together a Monte Carlo simulation using built-in functions can lead to errors. References Balakrishnan, N. R. (2013). Managerial decision modeling with spreadsheets (3rd ed.). Upper Saddle River: Prentice Hall. Oracle. (2018). Oracle® Crystal Ball User's Guide. Retrieved from www.oracle.com: https://docs.oracle.com/cd/E57185_01/CYBUG/ch02.html Discussion 8 Wesley Klein posted Sep 4, 2018 1:05 PM Monte Carlo simulation A simulation that experiments with probabilistic elements of a system by generating random numbers to create values for those elements. (Render 453) Crystal Ball An add-in for Excel that simplifies the implementation and solution of simulation models. (Render 453) In a general Monte Carlo simulation, the idea is that a random number be generated to see if it will work in the simulation. This is of course not feasible in basically any instance and certainly not for an organizational need and the like. If a refrigerator factory needs to determine how many condensers they will need for the next 6 months, they cannot simply guess a random number and hope it works out. They need a lot more input to make sure their are correct in their choices. References: Render, B. (2013). Managerial Decision Modeling with Spreadsheets, 3rd Edition. [MBS Direct]. Retrieved from https://mbsdirect.vitalsource.com/#/books/97801334682 05/

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School: University of Virginia


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Monte Carlo and Crystal Ball Simulation Response
Response to Kanija Sayles’ Post
Thank you for your post. First, I agree that the examples you have used for both Monte
Carlo and Crystal Ball are appropriate. Using Monte Carlo for determining the number of boiler
tubes required by the maintenance department is very appropriate since in...

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