Application of the Queuing Theory in the Encoding and Paying Processes of the Enrolment System in TIP-QC

Jaypy  T. Tenerife,; Manuel  Mendoza,

Application of the Queuing Theory in the Encoding and Paying Processes of the Enrolment System in TIP-QC

Discipline: Technology

Abstract:

The application of Queuing Theory in the encoding and paying process of the enrolment system in TIP-QC gives illustration to the traffic flow, scheduling, facility and employee allocation for the existing mobilization procedure. The study was able to solve for the correct algorithm of the enrolment procedure, which also represents the process of computing linguistics and related disciplines of Quantitative Management. The investigation was able to come-up with a complete mathematical analysis of several related processes including arriving at the queue, waiting in the queue and the service provided at the queue. Relevant to this, the theory permits the derivation and calculation of several performance measures including the average waiting time in the line, the expected number waiting or receiving service and the probability of encountering the structure in certain states, such as: empty of unfilled; full or occupied; having an available server; or having to wait with a certain time to be served.

Queuing Theory provides a systematic and logical approach to decision-making and permits a thorough analysis of solution involving uncertainty. It also amplifies the effectiveness of the decisions and enables quick recognition of best available solution. One reason that queuing analysis is important is that customers regard waiting pessimistically. Customers may tend to associate and relate this with poor service quality, especially if the delay is long. Since most people do not have intuitive appreciation of random processes and the role that they play in managerial decision and systems improvements, systems designers must weigh the cost of providing a given level of service capacity against implicit cost of having customers wait for service. The results of queuing analysis can be used in the context of a cost optimization model, where the sum of the cost of offering and the service and waiting is minimized.