Improving Addis Ababa Light Railway Transit Service Using Queue Theory and Monte-Carlo Simulation Models: Case of Torhailoch And Lideta Stations
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Date
2019-09
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Addis Ababa University
Abstract
One of the main problems of Addis Ababa light railway transit service is the
congestion and extended waiting line. The waiting time of passengers took on
average 17 minutes, greatly reducing the satisfaction of customers. This is the
reason why the study set the main objective to develop an optimization model for
improving the service of AALRT station. As part of the approach to achieve this
objective, the study first developed the characteristics of the data to investigate
the congestion problem. second, an optimization model developed on the selected
station. And finally, the researcher designed an alternative model through
comparing the performance and cost-effectiveness against the existing model.
The study adopted case study research methodology by taking the Torhailoch and
Lideta metro station using combined Queuing Theory and Monte-Carlo simulation
method. Moreover, the case studies were selected for the most congested station
in the morning’s and afternoon’s peak hours. Based on this, primary data were
collected from each station and secondary data were conducted from document
and through interview.
The best fit probability distributions of the passengers were found to be uniform,
binomial and negative binomial. These indicates that the congestion problem
cannot be solved through Queue Theory and Markov Chain. Hence, the
researcher optimized the problem by combining Queuing Theory and Monte Carlo
simulation. The models output indicates that the congestion rate of AALRT in
Torhailoch and Lideta are 109.13% - 115.76% and 116.18% -131.06%,
respectively.
Therefore, it was found that adding two single tramcars could reduce the waiting
time by seven minutes and the congestion by 95%. As well, the new model
improved the profit by $4,152.25 and $3,623.22 per hour in the morning and
afternoon, respectively.
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Keywords
Optimization, Queue Theory, Markov Chain, Monte Carlo Simulation, Waiting Time