...INTRODUCTION: The purpose of this paper is to bring out the use of Simulation by Managers of various organizations. Under discussion will be: Definition of simulation. Model construction. When and why it becomes handy to use simulation. Steps used in simulation technique. Random selection in simulation. Advantages / benefits derived from use of simulation technique. Disadvantages /Challenges associated with simulation technique. Role of computer in simulation. Conclusion / comments. Definition of simulation: Simulation can be defined as a quantitative technique which describes a process by developing a model of that process and then conduct a series of organized trial and error experiments to predict the behavior of the process through time often with the aid of a computer. It is a method that is used to solve a problem in many areas of management, for example inventory management, queuing problems, profit analysis and project management among others. Model construction: A successful simulation model has to be carefully designed in order to achieve the intended predictive purpose. Therefore important factors have to be considered such as; i. It must be objective oriented. It must be constructed for a purpose and be able to achieve that purpose. ii. Critical variables and relationships. These must be identified and incorporated in model. However it is not essential or indeed desirable to include all variables in the model. iii. Simplicity...
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...Brooklyn Warren Chapter 10 Simulation Modeling What is Simulation? * To try to duplicate the features, appearance, and characteristics of a real system. * Imitate a real-world situation mathematically. * Study its properties and operating characteristics. * Draw conclusions and make action decisions based on the results. Processes of Simulation: 1. Define Problem 2. Introduce Important Variables 3. Construct Simulation Model 4. Specify Values of Variables to Be Tested 5. Conduct the Simulation 6. Examine the Results 7. Select Best Course of Action Advantages of Simulation: * Straightforward and flexible. * Can handle large and complex systems. * Allows "what-if" questions. * Does not interfere with real-world systems. * Study interactions among variable. * "Time comparison" is possible. * Handles complications that other methods can't. Disadvantages of Simulation: * Can be expensive and time consuming. * Does not generate optimal solutions. * Managers must generate all conditions and constraints. * Each model is unique. Monte Carlo Simulation: Can be used with variables that are probabilistic. Steps: * Establish the probability distribution for each random variable. * Use random numbers to generate random values. * Repeat for some number of replications. Probability Distributions: Historical data Goodness-of-fit tests for common distributions: ...
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...Simulation technology can have countless benefits to all the eager students out there. It can, "Simulation is a technique, not a technology, to replace or amplify real experiences with guided experiences, often immersive in nature, that evoke or replicate substantial aspects of the real world in a fully interactive fashion," (Aebersold & Tschannen, 2013). It allows the students to be apart of a bigger picture than just the words in their textbooks. The simulation experience can also be recorded, therefore it allows students to backtrack on their prior experience and review it. They can see what they have done well and what could use some slight alterations to improve their skills. "A large body of research shows that simulation is incredibly effective as a teaching methodology and can contribute both to better patient outcomes and a culture of safety among nursing staff, " (American...
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...In “Are you living in a computer simulation?”, Nick Bostrom presents a probabilistic analysis of the possibility that we might all be living in a computer simulation. He concludes that it is not only possible, but rather probable that we are living in a computer simulation. This argument, originally published in 2001, shook up the field of philosophical ontology, and forced the philosophical community to rethink the way it conceptualizes “natural” laws and our own intuitions regarding our existence. Is it possible that all of our ideas about the world in which we live are false, and are simply the result of our own desire to believe that we are “real”? Even more troubling, if we are living in a computer simulation, is it possible that the simulation might be shut off at any moment? In this paper, I plan to do two things. First, I hope to consider what conclusions we might draw from Bostrom’s argument, and what implications this might have for how we affect our lives. Second, I plan to discuss a possible objection to Bostrom’s argument, and how this might affect our personal probability for the possibility that we are living in a computer simulation. Bostrom begins his argument by making a few assumptions necessary to the probabilistic claims he makes. The first is substrate-independence. This is simply the claim that if we were able to model the mind with enough detail, then we would be able to create artificial minds capable of thought in the same way that we are...
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...Initial operations strategy Prior to the commencement of the simulation, we examined the 50 days of historical data to glean as much information as we could about the operations. We performed some analysis in Excel and created a dashboard to illustrate various data. Specifically, we regressed the prior 50 days of jobs accepted to forecast demand over the next 2 - 3 months within a 95% confidence interval. The yellow and grey lines represent the maximum and minimum variability, respectively, based on two standard deviations (95%). Exhibit 1: Forecasted and actual demand by Day 50 and Day 270 Our two primary goals at the beginning of the simulation were as follows: 1) Eliminate bottlenecks and increase capacity in order to meet forecasted demand 2) Decrease lead time to 0.25 days in order to satisfy Contract 2 and maximize revenue In order to achieve these goals, we would need to know the capacity and throughput time of the entire system. We used the time required by each machine to process a lot to calculate capacity per station and then capacity of the entire production line (380 kits/day or 6 orders/day). In Exhibit 2 we can observe that the capacity of the production line is given by the station that produces the least number of units per day. Exhibit 2: Capacity of the production line The Decisions We decided to work with the maximum variability of demand because there was a penalty for late jobs and because there was no revenue for orders that took more than “x”...
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...Interpretation of Modeling and Simulation Can there be a better fit for a company out there that uses Microsoft Excel to conduct modeling to simulate their business growth other than Microsoft itself? Microsoft has made billions of dollars selling their Microsoft Office Suites and their home computer operating systems around the world. They have become one of the largest and well known companies in the world. The way that I see it, is that Microsoft’s business model, in a nutshell, is to provide goods and services in the form of software and support to paying customers. One question that may be asked in this day an age is with the advances in cloud computing and Google’s “free” gadgets, will the traditional Microsoft’s business model come to an end? What will Microsoft’s business analysts do in order to change their business model? One can only imagine that it will need to be modeled and simulated first to avoid potentially expensive mistakes. I must start off by saying that before I started my Systems Modeling Theory online class through Strayer, I thought that it may just be one of the hardest classes to understand that I’ve ever taken throughout the course of my college career. I can say now after having completed the last nine weeks of class that I was correct. What’s hard, is not understanding the concepts of why businesses would use Excel models for their business growth but rather the actual use of Excel itself. With all of the bells and whistles...
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...Simulation 2 Write-Up During the simulation there were many different factors leading to varying results. One of the biggest causes for variation was in the performance of the worker. The worker had the impression that they were under a time constraint. The performance of the worker was usually kept constant until the last 5 or 10 drawings of cards, which is when the worker felt the pressure to draw cards faster. Another cause of variation was the shuffling of the worker. If the worker didn’t shuffle the cards thoroughly it would result in a varied outcome from normal results. This variation is considered a normal cause for variation because as the time constraint became more noticeable the workers would shuffle differently. This occurred more on the last few draws each round. One special cause occurred when the professor walked over to our workstation and had a conversation. This distracted the worker and simulated a special cause for variation. In order to improve the process, I would first designate a worker for shuffling the cards so we could eliminate time used passing the cards. This worker would then split the cards into two piles. Then I would assign two other workers the jobs of counting the cards after they have been separated. The workers would then both tell a single recorder the amounts to be recorded. This would be repeated with the designated shuffler. In order to assure that the second supplier is delivering the promised quality, we made a second...
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...The Mikes Bikes simulation is an exciting and interesting way to gain critical insights into the development of a business. By operating a simulated bicycle manufacturing corporation over a period of ten years was an opportunity to gain insights on a real entrepreneurial experience. It allowed us to expand on the ideas taught in class such as creating a business strategy and using tools like SWOT and Porter’s five forces. We had many assumptions initially regarding the procedures but gradually we could learn the basics by facing enough challenges and by trial and error method. These skills cannot be learned by the usual form of lecturing. Considering our team, this was our first comprehensive exposure to real business environment. Each...
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...Simulation is a technique for practice and learning that can be used in many nursing facilities to help trainees to learn different skills in training and communication. It is a technique to replace and amplify real experiences with guided ones that can help the trainee to develop essential skills while at work. Simulation-based learning can be the way to develop health professionals’ knowledge, skills, and attitudes, while protecting patients from high risks situations. Simulation-based medical education can be the basics which provides a valuable information in learning how to solve certain problems and issues in nursing. Simulation-based training techniques, tools, and strategies can be applied learning experiences, as well as be used as...
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...Monte Carlo Simulation The Monte Carlo Simulation encompasses “any technique of statistical sampling employed to approximate solutions to quantitative problems” (Monte Carlo Method, 2005). The Monte Carlo method simulates the full system many times, each randomly choosing a value for each variable from its probability distribution. The outcome is a probability distribution of the overall value of the system calculated through the iterations of the model. A standard approach to risk management of projects is outline by Project Management Institute (2004) that includes six processes: Risk Management Planning, Risk Identification, Risk Qualification, Risk Quantification, Risk Response Planning, and Risk Monitoring and Control. Monte Carlo is usually listed as a method to use during the Risk Quantification process to better quantify the risks to the project manager is able to justify a schedule reserve, budget reserve, or both to deal with issues that could adversely affect the project. Monte Carlo simulation, while not widely used in project management, does get some exposure through certain project management practices. This is primarily in the areas of cost and time management to quantify the risk level of a projects budget or planned completion date. In time management, Monte Carlo simulation may be applied to project schedules to quantify the confidence the project manager should have in the target competition date or total project duration. In cost management, the project...
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...The Uses of Simulation in the Military Week 1, Research Paper Simulation has been a part of the military for almost as long as war has been around. However the types of simulations that we use today are a modern invention. Generals have been creating and testing strategies in simulation for a long time. Today we have the technology to create virtual representations of a battle zones stocked with geographical landscapes, both hostile and non-hostile NPCs (non-playable characters) and controllable entities acting as the various soldiers and vehicles. Simulation is a great and a necessary tool for training your soldiers and winning the war, the most important of these simulations are wargames, field exercises and flight training. One of the oldest types of simulation in the military are Wargames. A wargame generally is a type of game or simulation that is designed to expose a player to concepts and aspects of war (University of Virginia, 1999). Wargames would have started at the time of the first organized war (University of Virginia, 1999). These games were most likely picking an action then taking that action testing it and then tweaking the plan to make it better (University of Virginia, 1999). Generals used this setting for many years, allowing them to come up with better strategies, therefor winning more battles. In 7th century India there was a wargame called Chaturanga, Chaturanga in many aspects is much like the game chess which is often played today. In the game each...
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...Simulation-based learning is a training method that involves imitating the circumstances regarding a real-life job through the use of representations and models, (Saks, Haccoun, 2013. Pg.178-179). This training method presents trainees with the opportunity to learn in an environment that resembles the real-life job while protecting them from any risks. Furthermore, it helps trainees develop the necessary knowledge and skills to perform the job effectively, (Lateef, 2010). It causes them to master the task, improve their problem-solving skills, and enhance their teamwork abilities, (Lateef, 2010). Simulation training is commonly used in training for dangerous jobs, such as jobs in medicine or the military. Medical training programs often...
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...Modeling Order Book Fluctuation by Monte Carlo Technique CONTENTS Page no. 1) Certificate 2 2) Acknowledgement 3 3) Abstract 5 4) Introduction 6 5) Simulation code 8 ➢ Order Book 8 ➢ Diffusion 9 ➢ Price and Annihilation 11 ➢ One Trade return 14 ➢ Waiting time between consecutive trades 16 ➢ Conditional return 19 ➢ Hurst curve 20 6) Results and Discussion 22 7) Summary 28 8) Future Prospects 29 9) References ...
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...Simulation of Sports Facilities at University of Cincinnati Campus Recreation Center By: Nikhil Shaganti MID: M07428499 MS- Business Analytics Carl.H. Lindner College of Business, University of Cincinnati Page | 1 Table of Contents Acknowledgments………………………………………………………………….3 List of Figures……………………………………………………………...............4 Objectives of the study………………………………………………......................5 About UC Campus Recreation Center…………………………………….............. 5 Scope of Simulation……………………………………………………….............. 6 Data Collection Fitting Distributions for Wait times…………………………………………8 Challenges Faced…………………………………………………………….9 Assumptions………………………………………………………………..10 Fitness Center Model…………………………………………………………….....9 Basic Model………………………………………………………………….9 Updated Model- More Realistic……………………………………………10 Swimming Pool Model……………………………………………………………13 Output Analysis…………………………………………………………………...14 Conclusion………………………………………………………………………...18 References………………………………………………………………………...19 Page | 2 Acknowledgements With sincere gratitude, I would like to express my special thank you to Professor Dr. W. David Kelton. This project would have never been completed without his direction, assistance, and encouragement. I would also like to thank my parents, for their endless support during each and every one of my life’s endeavors. Page | 3 List of Figures Figure 1. Triangular distribution observed in Input Analyzer for Fitness Center Wait times...…………………………………………...
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...TOPICS IN AD HOC AND SENSOR NETWORKS Simulations in Wireless Sensor and Ad Hoc Networks: Matching and Advancing Models, Metrics, and Solutions Ivan Stojmenovic, University of Birmingham and University of Ottawa ABSTRACT The objective of this article is to give advice for carrying out a proper and effective simulation activity for protocol design. It challenges some of the existing criticisms of simulation practices that emphasized validation aspects. This article advocates the use of simple models, matching assumptions and metrics in the problem statement and simulation to provide a basic “proof of concept,” and comparison with truly competing solutions, which is possible only after a thorough and critical literature review. Then the complexity of the models can be increased (one parameter at a time), revising the algorithms themselves by adapting them to new assumptions, metrics, and the corresponding simulation environment. Selected independent variables should explain performance under a wide range of scenarios. unclear which protocol will perform well under a wide range of scenarios. It is our view that each article should be judged on its overall contribution, including the assumptions used, theory developed, new algorithms introduced, protocol details, simulation results, and relevance to an ultimate goal of staying on a path toward creating applications. We begin with a literature review of existing criticism for simulation practices, and then discuss what we believe...
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