Mohammad Ehsanifar; Nima Hamta; Mahshid Hemesy
Abstract
This paper includes a simulation model built in order to predict the performance indicessuch aswaiting time by analyzing queue’s components in the real world under uncertain and subjective situation. The objective of this paper is to predict the waiting time of each customer in an M/M/C queuing ...
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This paper includes a simulation model built in order to predict the performance indicessuch aswaiting time by analyzing queue’s components in the real world under uncertain and subjective situation. The objective of this paper is to predict the waiting time of each customer in an M/M/C queuing model. In this regard, to enable decision makers to obtain useful results with enough knowledge on the behavior of system, the queuing system is considered in fuzzy environment in which the arrival and service times are represented by fuzzy variables. The proposed approach for vague systems can represent the system more accurately, and more information is provided for designing queueing systems in real life. Furthermore, simulation method is applied successfully for modeling complex systems and understanding queuing behavior. Finally, a numerical example as a case study in a banking system is solved to show the validity of developed model in the real situation.
M. Hajian Heidary; A. Aghaie
Volume 2, Issue 2 , December 2015, , Pages 1-12
Abstract
Nowadays, logistics and supply chain management (SCM) is critical to compete in the current turbulent markets. In addition, in the global context, there are many uncertainties which affect on the market. One of the most important risks is supplier disruption. The first step to cope with these uncertainties ...
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Nowadays, logistics and supply chain management (SCM) is critical to compete in the current turbulent markets. In addition, in the global context, there are many uncertainties which affect on the market. One of the most important risks is supplier disruption. The first step to cope with these uncertainties is quantifying them. In this regard many researches have focused on the problem but measurement of the risk in the global SCM is yet a challenge. In the uncertain conditions, simulation is a good tool to study the system. This paper aims to study a global supply chain with related risks and measurement of the risks using simulation. Global aspects considered in the paper are: 1- currency exchange rate, 2- extended leadtime for abroad supplies, 3- regional and local uncertainties. In this regard, two popular risk measurement approaches (VaR and CVaR) are used in the simulation of uncertainties in the global supply chain. Results showed that adopting risk averse behavior to cope with the uncertainties leads to the lower stockouts and also higher costs.