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Conceptual modeling

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De La Salle University-Manila
De La Salle University-Manila
Education
1 of 26
Modeling Variability ,[object Object],[object Object],[object Object],[object Object]
Generating Random Numbers ,[object Object],[object Object],[object Object],[object Object],[object Object]
Linear Congruential Method ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Using Random Numbers to generate events ,[object Object],[object Object],95 – 00 1 .05 6 90 – 94 .95 .05 5 75 – 89 .90 .15 4 35 – 74 .75 .40 3 10 – 34 .35 .25 2 00 – 09 .1 .10 1 Random Digit Assignment Cumulative Frequency Observed Frequency Service Time (minutes)
Random Variates ,[object Object],[object Object]
Example of a random variate generator
Conceptual Modeling
Conceptual Modeling ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Conceptual Modeling ,[object Object],[object Object],[object Object]
What is conceptual modeling? ,[object Object],[object Object]
Elements of Conceptual Modeling ,[object Object],[object Object],[object Object],[object Object]
Elements of Conceptual Modeling ,[object Object],[object Object]
Representing the Conceptual Model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Representing the Conceptual Model ,[object Object],Customers (inter arrival time) Queue Capacity Service (Service time distribution)
Representing the Conceptual Model ,[object Object],Customer Arrives Space in Queue? Queue for Service Customer Served Customer Leaves Server Available? No No Yes Yes
Framework for Conceptual Modeling Source: Simulation by Robinson, 2004 Inputs Experimental Factors Simulation Model Outputs Responses Model Objectives Problem Situation
Methods of Model Simplification ,[object Object],[object Object],[object Object],[object Object]
Simplification Approaches ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Guidelines for simplification ,[object Object],[object Object],[object Object]
Data Collection ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Types of Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Dealing with Unobtainable Data ,[object Object],[object Object]
Other Data Issues ,[object Object],[object Object],Time TBF1 Machine down time TBF2
Data Representing Unpredictable Variability (Random) ,[object Object],[object Object],[object Object],[object Object]
Verification and Validation ,[object Object],[object Object]
Case

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Conceptual modeling

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  • 6. Example of a random variate generator
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  • 16. Framework for Conceptual Modeling Source: Simulation by Robinson, 2004 Inputs Experimental Factors Simulation Model Outputs Responses Model Objectives Problem Situation
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  • 26. Case