Input Analysis

Input Analysis - Input Analysis Theresa M Roeder Spring...

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Unformatted text preview: Input Analysis Theresa M. Roeder Spring 2011 2 Distinguishing Features of Simulation Ø Time (CLK) Þ DYNAMIC focused on this aspect during the modeling section of the course Ø Pseudorandom variables (RND) Þ STOCHASTIC will focus on this aspect for most of remaining course 3 Example: Effect of Process Time Variability Ø M/G/1 queueing system: – iid exponential interarrival times with mean 1/l – iid general service times with mean 1/m and variance s 2 Ø Pollaczek Khintchine (P-K) Formula where r =l /m is traffic intensity c(s) = s /m is coefficient of variation ( 29 + -+ = 2 1 1 1 1 2 2 s c W S ρ λ μ 4 Selecting Input Models Ø No data available Ø Data available – Framework – Graphical tools – Statistical tools – Sensitivity analysis 5 Data Collection: General Concepts Ø Relevance :Degree of control Sensitivity Ø When : Need to observe fi early in study Need sensitivities fi late in study Ø Cost :Setup (include training and P.R.) Sample size (sensitivity) Ø Accuracy : Technique, skill, motivation, training, timing (Monday a.m.??),… 6 Data Collection, cont’d Ø Precision : Technique, etc. Sample size Sample interval (dependencies) Ø Analysis : Error control Verification Dependencies within data set Dependencies between data sets 7 Data Collection, cont’d Translation errors : Concept fi Definitions fi Data fi Statistics (service) fi (waiting time) fi (W[i]) fi ( ) W 8...
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This note was uploaded on 01/26/2012 for the course DS 408 taught by Professor Theresam.roeder during the Spring '12 term at S.F. State.

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Input Analysis - Input Analysis Theresa M Roeder Spring...

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