Case study: Logistical behavior in the use of urban transport using the monte carlo simulation method

Lorenzo Cevallos-Torres, Miguel Botto-Tobar

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

This study presents a proposal to determine solutions to the models of queue theory through the use of simulation. The main objective is to evaluate the number of people who arrive at a public transport service station in order to be able to minimize monetary losses, the product of the defection of the people of the waiting line of this station. To evaluate the model, we proceeded to use tools that allow simulating random values based on probability distributions; such as the Log-Normal probability distribution, and the Binomial distribution.

Original languageEnglish
Title of host publicationProblem-based learning: A didactic strategy in the teaching of system simulation
EditorsLorenzo Cevalles-Torres, Miguel Botto-Tobar
PublisherSpringer
Pages97-110
Number of pages14
ISBN (Electronic)978-3-030-13393-1
ISBN (Print)978-3-030-13392-4
DOIs
Publication statusPublished - 1 Jan 2019

Publication series

NameStudies in Computational Intelligence
Volume824
ISSN (Print)1860-949X

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  • Cite this

    Cevallos-Torres, L., & Botto-Tobar, M. (2019). Case study: Logistical behavior in the use of urban transport using the monte carlo simulation method. In L. Cevalles-Torres, & M. Botto-Tobar (Eds.), Problem-based learning: A didactic strategy in the teaching of system simulation (pp. 97-110). (Studies in Computational Intelligence; Vol. 824). Springer. https://doi.org/10.1007/978-3-030-13393-1_6