Sensitivity analysis helps to test the sensitivity of the optimum solution with respect to changes of the coefficients in the objective function, coefficients in the constraints inequalities, or the constant terms in the constraints.
For Example in the case study discussed:
The actual selling prices (or market values) of the two products may vary from time to time. Over what ranges can these prices change without affecting the optimality of the present solution?
Will the present solution remain the optimum solution if the amount of raw materials, production time, or storage space is suddenly changed because of shortages, machine failures, or other events?
The amount of each type of resources needed to produce one unit of each type of product can be either increased or decreased slightly. Will such changes affect the optimal solution ?
The Input or Arrival Process
•The input process is usually called the arrival process.
•Arrivals are called customers.
•We assume that no more than one arrival can occur at a given instant.
•If more than one arrival can occur at a given instant, we say that bulk arrivals are allowed.
•Models in which arrivals are drawn from a small population are called finite source models.
•If a customer arrives but fails to enter the system, we say that the customer has balked
The Output or Service Process
•To describe the output process of a queuing system, we usually specify a probability distribution – the service time distribution – which governs a customer’s service time.
•We study two arrangements of servers: servers in parallel and servers in series.
•Servers are in parallel if all servers provide the same type of service and a customer needs only pass through one server to complete service.
•Servers are in series if a customer must pass through several servers before completing service.
•The queue discipline describes the method used to determine the order