Lecture No. 26
Chapter 7
Contemporary Engineering Economics
Copyright 2010
Contemporary Engineering Economics, 5th edition, 2010
Flaws in Project Ranking by
IRR
At Issue: Can we
rank the mutually
exclusive projects by
the magnitude of its
IRR?
Assuming
Lecture No. 25
Chapter 7
Contemporary Engineering Economics
Copyright 2010
Contemporary Engineering Economics, 5th edition, 2010
Net Investment Test
What it is: A process to determine whether or not
a firm borrows money from a project during the
investmen
Lecture No.14
Chapter 4
Contemporary Engineering Economics
Copyright 2010
Contemporary Engineering Economics, 5th edition, 2010
A. Investment Basics
The three basic investment objects are:
growth, income, and liquidity.
Liquidity How accessible is your mo
Lecture No. 10
Chapter 4
Contemporary Engineering Economics
Copyright 2010
Contemporary Engineering Economics, 5th edition, 2010
Chapter
Opening
Story
Refinancing
Dilemma
Under what
situation, would
homeowners
benefit from
refinancing their
current
mortg
Lecture No. 9
Chapter 3
Contemporary Engineering Economics
Copyright 2010
Contemporary Engineering Economics, 5th edition, 2010
Composite Cash Flows
Situation 1: If you
make 4 annual
deposits of $100 in
your savings account
which earns a 10%
annual inter
InterestFormulas
(GradientSeries)
Lecture No.8
Chapter 3
Contemporary Engineering Economics
Copyright 2006
LinearGradientSeries
L(1 + i) iN 1O
i
P = GM
P
N i (1 + i) Q
N
2
= G( P / G, i, N )
P
N
GradientSeriesasaCompositeSeriesofaUniform
SeriesofNPayments
EconomicEquivalence
Lecture No.5
Chapter 3
Contemporary Engineering Economics
Copyright 2006
EconomicEquivalence
What do we mean by economic
equivalence?
Why do we need to establish an economic
equivalence?
How do we establish an economic
equivalence?
Eco
Random-Number
Generation
Properties of Random Numbers
Random Number, Ri, must be independently drawn from a
uniform distribution with pdf:
U(0,1)
1, 0 x 1
f ( x) =
0, otherwise
2
x
E ( R ) = xdx =
0
2
1
1
0
1
=
2
Figure: pdf for
random numbers
Two import
MONTECARLO (STATIC) SIMULATIONS
Examples
Monte-Carlo (Static) Simulation
Estimating profit on a sale promotion
Newsvendor problem
Estimating value
Approximating integrals
Profit on a Sale Promotion
Furniture Store
Unit cost: $175
Demand distribution : TRI
Hand Simulations
Christos Alexopoulos and Dave Goldsman
Georgia Institute of Technology, Atlanta, GA, USA
2/25/12
1 / 25
Outline
1
Monte Carlo Integration
2
Making Some
3
Single-Server Queue
4
(s, S ) Inventory System
5
Simulating Random Variables
2 / 25
INVENTORY SYSTEMS
Inventory Systems
Assume periodic review, i.i.d. random demands,
constant (possibly non-zero) lead times and full
backlogging.
When to order?
How much to order?
Inventory Costs
Ordering Cost
setup cost for placing an order, K
per-unit
INTRODUCTION TO SIMULATION
WHAT IS SIMULATION?
The imitation of the operation of a real-world process or
system over time
Most widely used tool (along LP) for decision making
Usually on a computer with appropriate software
An analysis (descriptive) tool
QUEUEING SYSTEMS
Queueing Systems
Entities
Population
Server
Waiting Line (Queue)
Finite vs.
Infinite
One line vs.
Multiple lines
One server vs.
multiple server
Characteristics
Interarrival and Service Times
Exponential (M)
Deterministic (D)
Erlang (E)
Ge
GAMBLERS RUIN in a FAIR GAME
Gamblers Ruin in a Fair
Game
In a fair game, let player A has a fortune of k and player B
has a fortune of l. At each iteration of the game, the winner
takes one unit from the loser. The game ends when one
player loses everyth
STOCHASTIC PROCESSES
Simulation Types
Static Simulation
Dynamic Simulation
Estimation of the mean of a
Estimation of a performance
random variable
Expected Profit
measure from a random process
Average Queue Length
Average Inventory Level
Shortage Prob
PART ONE
Introduction to
Discrete-Event System
Simulation
1
Introduction to Simulation
A simulation is the imitation of the operation of a real-world process or system over time. Whether done by hand or on a computer, simulation involves
the generation of
Simulation Examples
Chapter 2
Examples (in book)
Queueing systems
Single server (ex. 2.1)
Two server (ex. 2.2)
Inventory system (section 2.3,ex. 2.3)
Monte Carlo simulation (like ex. 2.6)
Reliability (ex 2.5)
1 Server Queue
Calling population
Queue