17.4 Steady-State Probabilities and Mean Return Times of Ergodic Chains
Example 17.4-2
'denISons
,r the
j imabili-
(Cost Model)
Consider the gardener problem with fertilizer (Example 17.1-3). Suppose that the cost of the fertilizer is $50 per bag and the
18.1
Unconstrained Problems
667
We show by contradiction that Vf(X o) must vanish at a minimum point Xo. For
suppose it does not, then for a specific j the following condition will hold.
af(Xo)
af(X o)
-<Oar
>0
aXj
aXj
By selecting h j with appropriate si
MODULE 11
DOCUMENTS ON WEB
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING UNIT 1
11.1.1 In
MODULE 14
CASE TOOLS
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct. Pick the correct
answer. Do not guess. A key is given at the end of the module for you to verify your
answer
1. The expansion of CASE tools
MODULE 12
CONTROL,AUDIT AND SECURITY OF
INFORMATION SYSTEM
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your
MODULE 10
DESIGNING OUTPUTS
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct. Pick the correct
answer. Do not guess. A key is given at the end of the module for you to verify your
answer
LEARNING UNIT 1
10.1.1
(
MODULE 9
OBJECT-ORIENTED SYSTEM
MODELLING
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING U
MODULE 6
PROCESS SPECIFICATION
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING UNIT 1
6.1.1
MODULE 8
LOGICAL DATABASE DESIGN
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING UNIT 1
8.1
MODULE 7
DATA INPUT METHODS
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING UNIT 1
7.1.1 A
MODULE 5
DATA FLOW DIAGRAMS
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING UNIT 1
5.1.1 In
MODULE 3
INFORMATION GATHERING
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING UNIT 1
3.1.1
MODULE 2
SYSTEMS ANALYSIS AND DESIGN LIFE
CYCLE
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct. Pick the
correct answer. Do not guess. A key is given at the end of the module for you to
verify your answer
LEAR
MODULE 4
FEASIBILITY ANALYSIS
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct. Pick the correct
answer. Do not guess. A key is given at the end of the module for you to verify your
answer
LEARNING UNIT 1
4.1.1
MODULE 1
INFORMATION FOR MANAGEMENT
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct. Pick
the correct answer. Do not guess. A key is given at the end of the module for you
to verify your answer
LEARNING UNIT 1
System Analysis and Design/Case Study
Learning Objectives
Learning Objectives
In this module we will learn using two examples
How an informal description of a problem is analyzed to obtain a more formal
specification of requirements.
How various technique
MODULE 8
LOGICAL DATABASE DESIGN
Contents
1. MOTIVATION AND LEARNING GOALS
2. LEARNING UNIT 1
Entity-relationship(E-R) modelling of data elements of an
application.
3. LEARNING UNIT 2
Organization of data as relations
4. LEARNING UNIT 3
Normalization of r
MODULE 13
ELECTRONIC COMMERCE
OBJECTIVE QUESTIONS
There are 4 alternative answers to each question. One of them is correct.
Pick the correct answer. Do not guess. A key is given at the end of the
module for you to verify your answer
LEARNING UNIT 1
13.1.1
MODULE 13
ELECTRONIC COMMERCE
Contents
1. MOTIVATION AND LEARNING GOALS
2. LEARNING UNIT 1
What is E-Commerce?
3. LEARNING UNIT 2
Electronic Data Interchange
4. LEARNING UNIT 3
Security of E-Commerce
5. LEARNING UNIT 4
Payment in E-Commerce
6. REFERENCES
3.6
Sensitivity Analysis
129
(b) If the revenue per ton of exterior paint remains constant at $5000 per ton, determine
the maximum unit revenue of interior paint that will keep the present optimum solution unchanged.
(c) If for marketing reasons the unit
17.6
Analysis of Absorbing States
661
The top row of (I - Nr l gives the average number of visits in each station for a part starting at machine I. Specifically, machine I is visited 1.07 times, inspection I is visited 1.02 times,
machine II is visited .9
17.5
13.34
ld J.t23
First Passage Time
657
default state codes in row 6 with a code of your choice. The code will then be transferred
automatically throughout the spreadsheet. After you enter the transition probabilities,
step 3 creates the matrix I - P.
17.2
re
Absolute and n-Step Transition Probabilities
645
Example 17.2-1
In-
The following transition matrix applies to the gardener problem with fertilizer (Example 17.1-3):
2
1
1(.30
P = 2 .10
3 .05
d by2
3
.60
.60
.40
.10)
.30
.55
yed by
The initial con
E
~
.
~j
'j
18.2
:"'I1
Constrained Problems
681
"1
ill 10-
~
The reason the solution above does not yield the optimum solution is that the
specific choices of Y and Z are not optimum. In fact, to find the optimum, we need to
keep on altering our choices o
CHAPTER
4
Duality and Post-Optimal
Analysis
Chapter Guide. Chapter 3 dealt with the sensitivity of the optimal solution by determining the ranges for the model parameters that will keep the optimum basic solution
unchanged. A natural sequel to sensitivity
3.6
Sensitivity Analysis
145
3. Baba Furniture Company employs four carpenters for 10 days to assemble tables and
chairs. It takes 2 person-hours to assemble a table and .5 person-hour to assemble a chair.
Customers usually buy one table and four to six c
3.6
Sensitivity Analysis
139
*(e) If the available number of chips is reduced to 350 units, will you be able to determine the new optimum solution directly from the given information? Explain.
(f) If the availability of capacitors is limited by the feasib
3.6
Sensitivity Analysis
141
As we did for the right-hand side sensitivity analysis in Section 3.6.2, we will first
deal with the general situation in which all the coefficients of the objective function are
changed simultaneously and then specialize the
3.6
Sensitivity Analysis
137
prices per unit of solutions A and Bare $8 and $10, respectively. The daily demand for solution A lies between 30 and 150 units, and that for solution B between 40 and 200 units.
(a) Find the optimal amounts of A and B that Ch