Waiting Line Model

Sidonia Otilia Cernea et al. [2010] deals with the presentation of the single-channel waiting line systems with Poisson arrivals and exponential service times. Authors merely presented the single-channel waiting line model, with example on a fast-food restaurant. It is found that, the waiting line models play a key role in highlighting the operations effectiveness and hence the need of improving their characteristics. In order to improve the operations within the waiting line, either increase the average service rate or add new service channels.[22]

Mathias Dharmawirya et al. [2011] showed that queuing theory satisfies the model when tested with a real-case scenario. Authors obtained the data from a restaurant in Jakarta, then derive the arrival

Massey et al. [2002] reported that time dependent behavior has an impact on the performance of telecommunication models. These problems and more motivate the development of a queuing theory with time varying rates. Queuing theory as discussed in this paper is organized and presented from a communications perspective. Canonical queuing models with time-varying rates are given and the necessary mathematical tools are developed to analyze them. Finally they illustrate the use of these models through various telecommunication applications.[127]

2.2.2.11 Transportation

Alexandre G [1998] discussed the implications of high-capacity aircraft on the passenger departure lounge. Using deterministic queuing theory, Authors presented some analytical methods to evaluate possible solutions and to assess both the lounge area and the number of seats which minimize the overall cost of the lounge. The use of a spreadsheet to implement the methods is also explained.[2]

Hesham Rakha et al. [2000] demonstrated the consistency in delay estimates that are derived from queuing theory and shock-wave analysis and highlighted the common errors that are made in the literature with regards to shock-wave analysis delay estimation. It also demonstrated that the area between the demand and capacity curves can represent the total delay or the total vehicle-hours of travel if the two curves are spatially

Simulation-based approach had been applied to various areas related to transportation system and its feasibility had been reported as described in the Introduction. The simulation-based approach was also applied to the issues of traffic jams, but its key to success was very much relied upon the quality of the model. [100]

Using queuing analysis, Crispin Emmanuel D. Diaz [2005] showed that service type allocations do affect the level of delay in toll plazas. Authors demonstrated that it is possible to choose a service type allocation regime that will respond best to a given demand scenario. By choosing the appropriate allocation of service types like manual or E-PASS among available lanes for a toll plaza, the plaza service capacity can be maximized and delays minimized.