Accounting Final

Front 1

The case in which arriving customers refuse to join the waiting line

Back 1

Balking

Front 2

The population of items from which arrivals at the queing system come.

Back 2

Calling Population

Front 3

A queue discipline (meaning first-in, first-out) in which the customers are served in the strict order of arrival

Back 3

FIFO

Front 4

A method of classifying queuing systems based on the distribution of arrivals, the distribution of service times, and the number of service channels.

Back 4

Kendall Notation

Front 5

A case in which the number of customers in the system is a significant proportion of the calling population

Back 5

Limited or Finite Population

Front 6

A waiting line that cannot increase beyond a specific size.

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Limited Queue Length

Front 7

A set of relationships that exist for any queuing system in a steady state.

Back 7

Little's Equations

Front 8

Kendall notation for the constant service time model.

Back 8

M/D/1

Front 9

Kendall notation for the multichannel queuing model (with m servers) and Poisson arrivals and exponential service times

Back 9

M/M/m

Front 10

Kendall notation for the single-channel model with Poisson arrivals and exponential service times.

Back 10

M/M/1

Front 11

A system that has more than one service facility, all fed by the same single queue.

Back 11

Multichannel Queuing System

Front 12

A system in which service is received from more than one station, one after the other

Back 12

Multiphase System

Front 13

A probability distribution that is often used to describe random service times in a service system

Back 13

Negative Exponential Probability Distribution

Front 14

Descriptive characteristics of a queuing system, including the average number of customers in a line and in the system, the average waiting times in a line and in the system, and percent idle time

Back 14

Operating Characteristics

Front 15

A probability distribution that is often used to describe random arrivals in a queue.

Back 15

Poisson Distribution

Front 16

The rule by which customers in a line receive service

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Queue Discipline

Front 17

The mathematical study of waiting lines or queues

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Queuing Theory

Front 18

The case in which customers enter a queue but then leave before being serviced

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Reneging

Front 19

The cost of providing a particular level of service

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Service cost

Front 20

A system with one service facility fed by one queue

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Single-channel Queuing System

Front 21

A queuing system in which service is received at only one station

Back 21

Single-phase system

Front 22

The normal, stabilized operation condition of a queuing system

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Steady state

Front 23

The initial condition of a queuing system before a steady state is reached

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Transient state

Front 24

A calling population that is very large relative to the number of customers currently in the system

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Unlimited or Infinite Population

Front 25

A queue that can increase to an infinite size

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Unlimited Queue Length

Front 26

The proportion of the time that service facilities are in use

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Utilization Factor

Front 27

The cost to the firm of having customers or objects waiting to be serviced

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Waiting Cost

Front 28

One or more customers or objects waiting to be served

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Waiting Line(Queue)

Front 29

A simulation model in which the system status is updated at specific intervals of time

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Fixed time Increment Model

Front 30

A graphical means of presenting the logic of a simulation model. It is a tool that helps in writing a simulation computer program

Back 30

Flow Diagram or flowchart

Front 31

Computer programming languages, such as Visual Basic, C++, or java, that are used to simulate a problem

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General-Purpose languages

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Simulations that experiment with probabilistic elements of a system by generating random numbers to create values for those elements

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Monte Carlo Simulation

Front 33

A simulation model in which the system status is updated whenever the next event occurs

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Next Event Time Increment Model

Front 34

The use of simulation in competitive situations such as military games and business or management games

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Operational Gaming

Front 35

These graphical programs are prestructured to handle a variety of situations

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Prewritten Simulation Programs

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A number whose digits are selected completely at random

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Random Number

Front 37

A range of random numbers assigned to represent a possible simulation outcome.

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Random Number Interval

Front 38

A quantitative analysis technique that involves building a mathematical model that represents a real-world situation. The model is then experimented with to estimate the effects of various actions and decisions

Back 38

Simulation

Front 39

Programming languages especially designed to be efficient in handling simulation problems. The category includes GPSS/H, SIMSCRIPT II.5, and SLAM II

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Special-Purpose Simulation Languages

Front 40

Simulation models dealing with the dynamics of large organizational or governmental systems.

Back 40

Systems Simulation

Front 41

The process of comparing a model to the real system that it represents to make surethat it is accurate

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Validation

Front 42

The process of determining that the computer model is internally consistent and following the logic of the conceptual model

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Verification

Front 43

A state that, when entered, cannot be left. The probability of going from an absorbing state to any other state is 0.

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Absorbing State

Front 44

A condition that exists whent he state probabilities for a future period are the same as the state probabilities for a future period are the same as the state probabilities for a previous period

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Equilibrium Condition

Front 45

A matrix that is the inverse of the I minus B matrix. It is needed to compute the equilibrium conditions when absorbing states are involved.

Back 45

Fundamental Matrix

Front 46

The fraction of the population that shops at a particular store or market. When expressed as a fraction, market shares can be used in a place of state probabilities

Back 46

Market Share

Front 47

A type of analysis that allows us to predict the future by using the state probabilities and the matrix of transition probabilities

Back 47

Markov Analysis

Front 48

A matrix containing all transition probabilities for a certain process or system

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Matrix of Transition Probabilities

Front 49

The probability of an event occuring at a point in time. Examples include the probability that a person will be shopping at a given grocery store during a given month.

Back 49

State Probability

Front 50

The conditional probability that we will be in a future state given a current or existing state.

Back 50

Transition Probability

Front 51

A collection or vector of all state probabilities for a given system or process. The vector of state probabilities could be the initial state or future state.

Back 51

Vector of State Probabilities