Queueing theory models systems with queues that form due to demand for services exceeding the system's capacity. It was originally developed to model telephone traffic congestion. Key components of queueing systems include the arrival process, queue discipline, service mechanism, and outlet. Common models include the M/M/1 queue with a single server and Poisson arrivals, and the M/M/m queue with multiple servers. Queueing theory aims to minimize waiting times and costs by understanding the tradeoff between service levels and waiting.
MCM,MCA,MSc, MMM, MPhil, PhD (Computer Applications)
Working as Associate Professor at Zeal Education Society, Pune for MCA Progrmme.
Having 18 Years teaching experience
MCM,MCA,MSc, MMM, MPhil, PhD (Computer Applications)
Working as Associate Professor at Zeal Education Society, Pune for MCA Progrmme.
Having 18 Years teaching experience
This presentation is made to represent the basic transportation model. The aim of this presentation is to implement the transportation model in solving transportation problem.
Queueing theory is the mathematical study of waiting lines, or queues. A queueing model is constructed so that queue lengths and waiting time can be predicted
This presentation is made to represent the basic transportation model. The aim of this presentation is to implement the transportation model in solving transportation problem.
Queueing theory is the mathematical study of waiting lines, or queues. A queueing model is constructed so that queue lengths and waiting time can be predicted
Waiting Line Model is one of the decision line model.Waiting Line Model is one of the decision line model.Waiting Line Model is one of the decision line model.Waiting Line Model is one of the decision line model.
Solving Of Waiting Lines Models in the Bank Using Queuing Theory Model the Pr...IOSR Journals
Waiting lines and service systems are important parts of the business world. In this article we describe several common queuing situations and present mathematical models for analyzing waiting lines following certain assumptions. Those assumptions are that (1) arrivals come from an infinite or very large population, (2) arrivals are Poisson distributed, (3) arrivals are treated on a FIFO basis and do not balk or renege, (4) service times follow the negative exponential distribution or are constant, and (5) the average service rate is faster than the average arrival rate. The model illustrated in this Bank for customers on a level with service is the multiple-channel queuing model with Poisson Arrival and Exponential Service Times (M/M/S). After a series of operating characteristics are computed, total expected costs are studied, total costs is the sum of the cost of providing service plus the cost of waiting time. Finally we find the total minimum expected cost.
Queuing theory: What is a Queuing system???
Waiting for service is part of our daily life….
Example:
we wait to eat in restaurants….
We queue up in grocery stores…
Jobs wait to be processed on machine…
Vehicles queue up at traffic signal….
Planes circle in a stack before given permission to land at an airport….
Unfortunately, we can not eliminate waiting time without incurring expenses…
But, we can hope to reduce the queue time to a tolerable levels… so that we can avoid adverse impact….
Why study???? What analytics can be drawn??? Analytics means ---- measures of performance such as
1. Average queue length
2. Average waiting time in the queue
3. Average facility utilization….
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2. Murphy's Law
If you change queue, the one that you
left will start to move faster than
the one you are in now.
Your queue always goes the slowest.
Whatever queue you join, no matter
how short it looks, it will always take
the longest to you to get served.
3. History of queueing theory
Developed to provide models for forecasting
behaviors of systems subject to random demand
The first problems addressed concerned congestion
of telephone traffic
Erlang observed that a telephone system can be
modeled by Poisson customer arrivals and
exponentially distributed service times
Molina, Pollaczek, Kolmogorov, Khintchine, Palm,
Crommelin followed the track
5. Queues/ waiting line
▪Common phenomenon of everyday life
▪Line maybe People / Items
▪Examples
– Grocery shop, Bank, Petrol refilling units, Automobile Service
station, Airplane, Train etc.
6. Queue
The line that forms in front of
service facilities is called a queue or
a waiting line
It involves arriving customers (or
items) who wait to utilize the
services at the facility which provide
the service they require
Departure of served
customers
Departure of impatient customers
Customer
arrivals
7. Queueing theory
A branch of the operations research providing probabilistic modelling tools
for Queueing Systems
Defined as the construction of mathematical models of various types of
queuing system so that predictions may be made about how the
systems will cope with demands made upon it
10. Queueing system
A very simple mechanism
Customers arrive at service counter and are attended by
one or more of the service counters
As soon as a customer is served, he departs from the
system
Arrivals
Queue
Service
Outlet
11. Components/Characteristics of queueing system
1.The input process or arrival process
2.The Queue discipline or Waiting line
3.The Service mechanism
4.The Outlet of the queue
12. The input process or arrival process
Arrival from the input population may be classified based on
a.Size of the calling population
b.Pattern of arrivals at the system
c.Behavior of the arrivals
13. a. Size of the calling population
▪Can be finite / infinite
▪Infinite
–Cars arriving at toll booth
–Shoppers arriving at a supermarket
▪Finite
–Fleet of 4 cars visiting a repair shop
–A milling unit with three mills which require service from time to time
14. b. Pattern of arrivals at the system
▪Organized pattern/ random order
▪No. of arrivals per unit time estimated by Poisson
distribution
P(x) = e-λ λx
x!
◦ λ = the average arrival rate per time unit
◦ P(x) = the probability of exactly x arrivals occurring during one
time period
16. c. Behavior of the arrivals
▪Customer attitude about getting into line differs
▪Balking customer refuse to join the line because it is too long to suit
their needs or interest
▪Reneging customer enters the queue but they become impatient and
leave without completing their transaction
▪Jockeying customers move from one queue to another hoping to
receive service more quickly
17. 2. The Queue discipline or Waiting line
▪Length of line unlimited/ limited
▪A queue is limited when it cannot by law or physical
restrictions increase to an infinite length. Ex. Small
restaurant
▪A queue is unlimited when its size is unrestricted, as in case of
the toll booth serving arriving automobiles
19. 3. The Service mechanism
◦ Two aspects
a.Structure of the service system
b.Speed of service
20. Structure of the service system
How the service facilities are arranged
i.A single facility
ii.1 queue – several service facility
iii.Multichannel facility
iv.Multi-stage channel facility
21. b. Speed of service
Speed of service can be expressed in 2 ways:
i.Service rate
–No. of customers during a particular period of time
ii.Service time
–The amount of time required to service a customer
–Generally assumed to be exponentially distributed about
average service time
23. 4. The Outlet of the queue
▪No problem in single channel facility whereas,
▪Problem in multistage channel facility
▪Service station breakdown can have effect on the queues
▪Line before the breakdown will lengthen and the line
following the breakdown will diminsh
25. Kendall’s Notation
A/B/m/K/N/D
A Arrival Process M: Markovian D: Deterministic Er:
Erlang G: General
B Service Process M: Markovian D: Deterministic Er:
Erlang G: General
m Number of servers m=1,2,…
K Storage Capacity K= 1,2,… (if œ †hen i† is omified)
N Number of customers N= 1,2,…
(for closed networks otherwise it is omitted)
D Queueing Discipline FCFS,LCFS,SIROetc. Default is FCFS
26. Commonly used Queueing models
Model Queue characteristic Example
M/M/1/∞ Single server, discouraged
Arrivals
Single help Desk or counter in
store
M/M/m/∞ m servers, infinite number of
waiting positions
Airline ticket counter
M/M/m/m m server loss system, no waiting Automated car wash facility
M/M/1/K Single server queue with K
waiting positions
Mechanic shop
M/M/1/-/N Single server, infinite number of
waiting positions, finite customer
population N
Receiving degree in
Convocation