Queueing theory in massive transportation

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SUMMARY

The discussion focuses on modeling the bus waiting process in Bogota's massive transportation system using queueing theory. The user proposes a G/G/100/100 model to represent a bus with a capacity of 100 people. However, the effectiveness of this model is questioned, as it requires a clear explanation of how the model components correspond to real-world elements. The conversation emphasizes the importance of defining the purpose of the model to determine its appropriateness.

PREREQUISITES
  • Understanding of queueing theory concepts, specifically G/G/n/n systems
  • Familiarity with simulation tools for complex environments
  • Knowledge of bus transportation systems and capacity management
  • Ability to translate real-world scenarios into mathematical models
NEXT STEPS
  • Research G/G/n/n queueing models and their applications in transportation
  • Explore simulation tools like AnyLogic or Simul8 for complex system analysis
  • Learn about capacity management strategies in public transportation systems
  • Investigate how to visualize queueing models effectively for stakeholder presentations
USEFUL FOR

Transportation analysts, urban planners, and anyone involved in optimizing public transportation systems using queueing theory and analytical modeling techniques.

jfimbett
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Hi

I'm working on a project trying to analize the massive transportation system in Bogota (Colombia). I know that simulation tools are better in complex environments but I want to try some analytic tools.

I was thinking how to model the process in which people wait for a Bus. But I don't know really how to model this process.

Suposse the capacity of the BUS is 100 people.

I was thinking of a system G/G/100/100. Am I correct?

Can anyone help me? Thank you.
 
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jfimbett said:
I know that simulation tools are better in complex environments
They are!

but I want to try some analytic tools.

I was thinking how to model the process in which people wait for a Bus. But I don't know really how to model this process.

You'll find that if you think clearly about how to create a simulation, you will be able to state all the information needed to do an analytic solution.

Suposse the capacity of the BUS is 100 people.

I was thinking of a system G/G/100/100. Am I correct?

Whether you are correct or not can only be determined if you use say what you are trying to use this model for. I don't see how you plan to visualize a bus as 100 servers. One cannot say whether a a model fits a situation unless the user explains how the components of the model map to the component parts of reality.
 

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