Risks and uncertainties are inherent in construction projects and if neglected these risks often lead to project cost and time overruns. To enable successful projects‚ companies follow a structured risk management process. The high complexity of the project demands for computer based tools. We will be examining and evaluating how contractor experts manage risks during the tendering process for large scale infrastructural projects. Our aim is to provide information that will aid to improve risk management support tool in the studied company
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(2011) © (2011) IACSIT Press‚ Bali‚ Indonesia Case Study for Restaurant Queuing Model Mathias Dharmawirya School of Information Systems Binus International – Binus University Jakarta‚ Indonesia mdharmawirya@binus.edu Erwin Adi School of Computer Science Binus International – Binus University Jakarta‚ Indonesia eadi@binus.edu busy fast food restaurant [3]‚ as well as to increase throughput and efficiency [5]. This paper uses queuing theory to study the waiting lines in Sushi Tei Restaurant
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Quasars A Quasi-stellar radio source‚ also known as a quasar‚ is an extremely distant nucleus to an active galaxy. They are the furthest objects away from our galaxy that can be seen‚ but are visible to us because they are the brightest matter in our universe. Quasars are known to have an extremely high redshift. Though we have not been observing quasars for long enough to determine how they are born‚ they are believed to have been formed by supermassive black holes consuming an enormous amount
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A QUEUEING SYSTEM STUDY FOR REFUELING SERVICE AT SHELL GASOLINE STATION OF MAHAYAG‚ ISABEL‚ LEYTE Undergraduate Thesis VISAYAS STATE UNIVERSITY Visca‚ Baybay City‚ Leyte‚ Philippines DENNIS RODADO ARAÑO Second Semester S.Y. 2009-2010 A QUEUEING SYSTEM STUDY FOR REFUELING SERVICE AT SHELL GASOLINE STATION OF MAHAYAG‚ ISABEL‚ LEYTE VISAYAS STATE UNIVERSITY Visca‚ Baybay City‚ Philippines DENNIS RODADO ARAÑO April 2010 VISAYAS STATE UNIVERSITY Visca‚ Baybay‚ Leyte 6521-A
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Mathematical modeling is commonly used to predict the behavior of phenomena in the environment. Basically‚ it involves analyzing a set of points from given data by plotting them‚ finding a line of "best fit" through these points‚ and then using the resulting graph to evaluate any given point. Models are useful in hypothesizing the future behavior of populations‚ investments‚ businesses‚ and many other things that are characterized by fluctuations. A mathematical model usually describes a
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USING COMPUTER SIMULATION MODELING TO REDUCE WAITING TIMES IN EMERGENCY DEPARTMENTS Igor Georgievskiy‚ Alcorn State University Zhanna Georgievskaya‚ Alcorn State University William Pinney‚ Alcorn State University ABSTRACT This paper examines the wide-spread problem of extended waiting times for health services‚ in the context of the Emergency Department (ED) at a regional hospital. In the first phase of the study‚ a field observation was conducted to document the current operation of the ED. The
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was a great deal of iteration between the cases studies and the literature. The objective was to identify important contextual factors that may moderate the impact of RFID. The second phase incorporated simulation modelling. This was a confirmatory study. The objective was to develop two simulation models of the cases from the previous phase‚ and as a result‚ verify the effects of particular contextual factors on process performance. Findings – As an outcome of this research‚ an initial subset of “warehouse
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Number: (443)956-6067 E-mail Address: surban1@jhu.edu Teaching Assistant Ben Brock: bbrock1@jhu.edu Office Hours Saturdays‚ 10:00am – 12:30pm at DC Center (room 201) or by appointment Required Text and Learning Materials: Stochastic Simulation and Applications in Finance with MATLAB Programs‚ (2008)‚ Huu Tue Huynh‚ Van Son Lai‚ Issouf Soumare (HLS) [this book may be available as an e-book for students] MATLAB: An Introduction with Applications 4th Edition (2010) or earlier Editions
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major insights collected in a retrospective comparative analysis of eight strategic projects in which ‘policy gaming’ was the major methodology. Policy gaming uses gaming-simulation to assist organizations in policy exploration‚ decision making and strategic change. The process combines the rigor of systems analysis and simulation techniques with the creativity of scenario building and the communicative power of role-play and structured group techniques. Reality is simulated through the interaction
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Table of Contents 1.0 Introduction 3 2.0 Current Simulation Model 3 2.1 Clock Options 3 2.2 The warm-up period 3 2.3 Results collection period 4 2.4 The number of trials used 4 2.5 Results analysis 4 3.0 Pooling Resources 5 3.1 The impact of pooling resources 5 3.2 Comparison between initial model and pooled model 6 4.0 Usefulness of Simulation Model in Business Context 6 4.1 Simulation and decision making 6 4.2 Researcher Recommendation
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