Non-Markovian bulk queueing system with state dependent arrivals and multiple vacations - a simulation approach

Modelling and simulation analysis of a bulk queueing system

“…Recently, Moazzami et al (2013) focussed on modelling the behaviour of a petrol station and they used WITNESS 2004 simulation software to model and analyze it. A Non-Markovian bulk queueing system with state dependent arrivals and multiple vacations was studied by Ramaswami and Jeyakumar (2014). They used ARENA software to model the system and derived some of the performance measures.…”

Multi-station manufacturing system analysis: theoretical and simulation study

“…A typical flexible manufacturing system configuration is chosen for detailed study and analysis. Ramaswami and Jeyakumar (2014) studied non-Markovian bulk queueing system with state dependent arrivals and multiple vacations using a simulation approach, Korytkowski and Wisniewski (2012) examined a multi-product production systems with in-line quality control, Rad et al (2014) gave an analysis of a manufacturing system using simulation and multi-criteria decision-making tools were applied, Hasan et al (2014) considered reconfigurable manufacturing systems to be one of the newer technologies which cannot only meet stochastic product demand but can also produce products having customised variety, Tajini et al (2014) developed a flexible modelling environment for the simulation and analysis of different production systems, Boualem et al (2015) focused on flexible production system modelled by re-entrant queueing network, where several performance measures have been investigated through expanded Monte Carlo simulations.…”

Measurable order and simulation

“…For example: Beskos et al (2006) provide an algorithm for exact simulation of a class of Itô's diffusions; Frisque et al (2006) simulate stochastic fluctuations of particles at mesoscopic level; Harrod and Kelton (2006) show three algorithms to simulate non-homogeneous Poisson processes with piecewise rate function; Manninen et al (2006) simulate solutions of stochastic differential equations; Özceyhan and Sen (2006) use random walks applied to particle tracking; in order to evaluate organ transplant policies, Pritsker et al (1995) simulate non-homogeneous Poisson processes having exponential rate functions which may include polynomial and trigonometric components; Salis et al (2006) developed a software for multiscale simulation problems; in Shannon (1975) can be found several simulation techniques for different kinds of problems; Szymczak and Ladd (2006) introduce algorithms that can be used to implement boundary conditions in stochastic simulations of the convection-diffusion equation; Yonglin and Jiafan (2006) simulate a time series of road irregularities; Ramaswami and Jeyakumar (2014) used the software ARENA to generate an M X /G(a, b)/1 queueing system with state dependent arrivals and multiple vacations; Zhang and Feng (1997) provide an approximate algorithm method which can be applied to generate continuous non-uniform statistical distributions; Choroma et al (2013) simulate the drying of Lake Chad; Florea and Nănu (2013) describe an algorithm for simulating retrial queuing systems; Hairer and Weare (2015) studied the modified diffusion Monte Carlo algorithm to generate the so called 'Brownian fan'; Magdziarz and Teuerle (2015) made the simulation of multidimensional Lévy walks. For example: Beskos et al (2006) provide an algorithm for exact simulation of a class of Itô's diffusions; Frisque et al (2006) simulate stochastic fluctuations of particles at mesoscopic level; Harrod and Kelton (2006) show three algorithms to simulate non-homogeneous Poisson processes with piecewise rate function; Manninen et al (2006) simulate solutions of stochastic differential equations; Özceyhan and Sen (2006) use random walks applied to particle tracking; in order to evaluate organ transplant policies, Pritsker et al (1995) simulate non-homogeneous Poisson processes having exponential rate functions which may include polynomial and trigonometric components; …”