Hurtado-Hernandez, Margarita
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Hurtado-Hernandez, Margarita
Official Name
Hurtado Hernández, Margarita María Elvira
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mhurtado
Hurtado Hernández, Margarita
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Scopus Author ID
56163023500
Researcher ID
GBM-3031-2022

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Reducing the variability of inter-departure times of a single-server queueing system : the effects of skewness

2019 , Romero-Silva, Rodrigo , Marsillac, Erika , Shaaban, Sabry , Hurtado-Hernandez, Margarita

A critical performance measure in serial production lines is the variability of inter-departure times of a single-server queue. Increasing upstream inter-departure time variability generates greater downstream variability, diminishing overall line performance. Theory suggests that the variability of inter-departure times of a single-server queue is reduced by decreasing the variance of inter-arrival and service times. This study investigates the effects of the skewness of inter-arrival and service time distributions on the variability of inter-departure times. Contrary to previous results suggesting that mean waiting times of a GI/G/1 queue can be reduced by increasing inter-arrival time skewness, this experimental study of a GI/G/1 queue with triangular inter-arrival and service times shows that the inter-departure time coefficient of variation is reduced through a combination of negative inter-arrival time skewness and positive service time skewness. These results also suggest that the absolute value of the negative autocorrelation between consecutive departures is reduced by the same combination of negative inter-arrival time skewness and positive service time skewness for low values of server's utilization, while positive skewness for both inter-arrival and service times reduces this value for high values of server's utilization. Finally, it was found that queue capacity constraints increase the coefficient of variation of inter-departure times, as has been previously suggested, as well as the skewness and the absolute correlation values of the inter-departure time distribution. © 2019 Elsevier Ltd

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Serial production line performance under random variation : dealing with the "law of variability"

2019 , Romero-Silva, Rodrigo , Marsillac, Erika , Shaaban, Sabry , Hurtado-Hernandez, Margarita

Many Queueing Theory and Production Management studies have investigated specific effects of variability on the performance of serial lines since variability has a significant impact on performance. To date, there has been no single summary source of the most relevant research results concerned with variability, particularly as they relate to the need to better understand the ‘Law of Variability’. This paper fills this gap and provides readers the foundational knowledge needed to develop intuition and insights on the complexities of stochastic simple serial lines, and serves as a guide to better understand and manage the effects of variability and design factors related to improving serial production line performance, i.e. throughput, inter-departure time and flow time, under random variation. © 2019 The Society of Manufacturing Engineers

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Exploiting the characteristics of serial queues to reduce the mean and variance of flow time using combined priority rules

2018 , Romero-Silva, Rodrigo , Shaaban, Sabry , Marsillac, Erika , Hurtado-Hernandez, Margarita

This paper addresses the trade-off challenge from reducing either the mean or variance of flow time when using simple sequencing rules in balanced, multi-class, serial queues. Study results show that instead of the expected zero sum situation, a balance between the two objectives can be achieved by assigning different priority rules to different queues. The order of priority rule assignments in different queues is shown to be relevant because variability along the line creates unbalanced queue lengths for each station, depending on the characteristics of the line. Thus, it was found that a simple heuristic for reducing both the mean and the variance of flow time in non-heavy traffic environments is to assign the first queue a priority rule that reduces its mean queue length while assigning the other queues a priority rule that reduces the variance of flow time. Conversely, for very-high traffic environments, performance improvements are shown from assigning the first queue a priority rule that reduces the variance of flow time while assigning the other queues a priority rule that reduces queue length. © 2017 Elsevier B.V.

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Studying the effects of the skewness of inter-arrival and service times on the probability distribution of waiting times

2020 , Romero-Silva, Rodrigo , Shaaban, Sabry , Marsillac, Erika , Hurtado-Hernandez, Margarita

Previous studies have shown that the mean queue length of a GI/G/1 system is significantly influenced by the skewness of inter-arrival times, but not by the skewness of service times. These results are limited because all the distributions considered in previous studies were positively skewed. To address this limitation, this paper investigates the effects of the skewness of inter-arrival and service times on the probability distribution of waiting times, when a negatively skewed distribution is used to model inter-arrival and service times. Subsequent to a series of experiments on a GI/G/1 queue using discrete-event simulation, results have shown that the lowest mean waiting time and the lowest variance of waiting times can be attained with a combination of positive inter-arrival skewness and negative service skewness. Results also show an interesting effect of the skewness of service times in the probability of no-delay in environments with a higher utilization factor. © 2020 Brazilian Operations Research Society.

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