e451c17109fe6ef4c69f687e4ccde6d78c48d516
Carrier Origin Destination Departure Delay Arrival Delay Total Delay Delay Status
AA
JFK
LAS
-5
-23
-28 N
AA
SFO
ORD
-5
-27
-32 N
AA
SFO
ORD
-1
-26
-27 N
AA
SFO
ORD
-9
-30
-39 N
AA
SFO
ORD
-9
-9
-18 N
AA
SFO
ORD
-6
5eaa26e1bd678e5105ccfe0d845f3a9db5a77767
Carrier
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
AA
Origin
JFK
SFO
SFO
SFO
SFO
SFO
SFO
SFO
SFO
SFO
SFO
c81499f18674dd524b8b8e761d79a03064d6b7f7
11/1/2015
AA
111 ORD LAX
1709
-1 1952
2 283
11/1/2015
AA
1092 ORD LAX
2021
-4 2243 -20 262
11/1/2015
AA
1081 ORD LAX
841
-4 1052 -33 251
11/1/2015
AA
1243 ORD LAX
705
-5
11/1/2015
AA
1358 ORD LAX
1508
-2 1739 -10 2
CASE STUDY: FASTEST AIRLINES (PART 1)
1. Objectives
The purpose of this study is to become familiarize with Python to perform basic data analysis.
There are many ways to assess the quality of an airline. You will learn how to assess airlines
based on hist
IE 300 HW6
Yuanling Gan
Coin Toss Experiment
An experiment: 100 tosses of a fair coin and
record the number of heads
Random variable X = the number of heads
in 100 coin tosses, each coin toss is a
Bernoulli Distribution p=0.5
Sample space: 0, 1, 2, , 100
Announcements
1.
2.
3.
4.
5.
Midterm during lecture hours (12:30-1:50pm) on Thu, Mar 17
Review problems posted in compass2g
Topics will include everything covered until (including)
the Assignment Problem
No cheat sheets allowed during the midterm
Seating
Plan for today
If no entering variable, optimum
reached
If no leaving variable, unbounded.
Recap: Transportation Problem, Solution method: Stage 1
Basic Feasible Solution for the Transportation Problem
Stage 2: Iterate to optimal solution
Unbalanced
Topic for the week
Dynamic Programming
Example 2: Project Assistant Allocation
Example 3: Employment Scheduling
Announcement
Homeworks are due on
Tuesdays henceforth
(Continuous decisions and states)
Example 4: Reject Allowance
(Decision dependent pro
Plan for the day
Announcement
Submit your homework
Dynamic Programming
Example 3: Employment Scheduling
before this slide disappears
(Continuous decisions and states)
Example 4: Reject Allowance
(Decision dependent probabilistic state transitions)
Exa
Topic for the week
Dynamic Programming
Example 1: Stagecoach
Terminologies
Announcement
Homeworks are due on
Tuesdays henceforth
Example 2: Project Assistant Allocation
Example 3: Employment Scheduling
(Continuous decisions and states)
Example 4: Re
INTRODUCTION
What is Operations Research
Operations Research (OR)
scientific approach to decision making
seeks to determine how best to design and operate a system
under conditions requiring the allocation of scarce resources
Provides a set of algori
Plan for today: Simplex Method
Example
Limitations
Simplex Method in Algebraic Form
Simplex Method in Tabular Form
Recap
Simplex Method: overview
Initialization
transform the original LP into the augmented LP, determine basic and non-basic variables
Topic for this week: Duality
Recap
SHADOW PRICES
Recap
Example
Example (from first lecture)
Company makes two products: glass door sells for $3 per batch, window sells for $5 per batch.
Working hours needed and the total hours available are given below:
d
Plan for today
Assignment Problem, Hungarian Algorithm
Network Optimization Models
Terminologies
Minimum Spanning Tree Problem
Announcements
3.
Midterm during lecture hours (12:30-1:50pm) on Thu, Mar 17
Review problems posted in compass2g
Topics will
Announcements
1.
Submit your homework before the beginning of the lecture
before this slide disappears
2.
Midterm during lecture hours (12:30-1:50pm) on Thu, Mar 17
Review problems posted in compass2g
Topics will include everything covered until
3.
4.
R
Plan for today
Dual Optimal Solution from the Simplex Tableau
Dual Simplex Method
Example
Recap
SHADOW PRICES
Shadow price of a constraint is the rate of objective
increase when the constraint is relaxed/tightened
Recap
Example
Primal Dual Connection
P
IE300, CL1, Midterm Exam 2, November 20
Name:
Discussion Section:
There are total of 5 problems on both side of this page.
Show all your works. All answers need to be written on the exam booklet, not here!
Write your name and discussion section on both
IE300, CL1, Final Exam Sample
Name:
Discussion Section:
1. 15 points The brightness of a television picture tube can be evaluated by measuring
the amount of current required to achieve a particular brightness level. The current is
normally distributed. A
Sample Exam- Midterm I
Problem 1.
On a given computer system, a password is required to be 7 characters long. The passwords can
contain any letters of the alphabet (lower and upper case), the numbers 0 - 9, and no special
characters.
(a) How many password
IE300 - Homework 5 (CL1)
Due: Monday, November 9, in class
Problem 1.
(10 pts) An article in the Journal of Structural Engineering (Vol. 115, 1989) describes an experiment to test the yield
strength of circular tubes with caps welded to the ends. The firs
IE300 - Homework 3 (CL1)
Due: Wednesday, October 7, in class
Problem 1. Train Station
Trains headed for destination A arrive at the train station at 15-minute intervals starting at 7 A.M., whereas
trains headed for destination B arrive at 15-minute interv
IE300 - Homework 7 (CLI)
Due: Wednesday; December 9, in class
Problem 1.
Consider the hypothesis test 1], :pz, = ,u, against H, :,u, :; rawith known variances o. = 10 and ti; = 5.
Suppose that sample siZes a; = 10 and H2 = 15 and that I, = 24.5 and E, = 2
IE300 - Homework 7 (CL1)
Due: Wednesday, December 9, in class
Problem 1.
Consider the hypothesis test H0 : 1 2 against H1 : 1 2 with known variances 1 = 10 and 2 = 5.
Suppose that sample sizes n1 = 10 and n2 = 15 and that x1 24.5 and x2 21.3. Use = 0.01.
Chapter 10 Selected Problem Solutions
Section 10-2
1) The parameter of interest is the difference in fill volume, 1 2 ( note that 0=0)
10-1. a)
2) H0 :
3) H1 :
1 2 = 0
1 2 0
or
or
1 = 2
1 2
4) = 0.05
5) The test statistic is
z0 =
( x1 x2 ) 0
2
1 2
+ 2
n1
125 375 5 0 2.3453E8 = = 0.00092 f X (5) = 2.5524 E11 500 5
b)
x f(x)
3-150.
0 1 2 3 4 5 6 7 8 9 10 0.0546 0.1866 0.2837 0.2528 0.1463 0.0574 0.0155 0.0028 0.0003 0.0000 0.0000
Let X denote the number of totes in the sample that exceed the moisture conte
CHAPTER 3 Section 3-1 3-1. 3-2. 3-3. 3-4. 3-5. The range of X is
cfw_0,1,2,.,1000
The range of X is cfw_0,12,.,50 , The range of X is cfw_0,12,.,99999 , The range of X is cfw_0,12,3,4,5 , The range of X is 1,2,.,491 . Because 490 parts are conforming, a n
CHAPTER 3 Section 3-1 3-1. 3-2. 3-3. 3-4. 3-5. The range of X is
cfw_0,1,2,.,1000
The range of X is cfw_0,12,.,50 , The range of X is cfw_0,12,.,99999 , The range of X is cfw_0,12,3,4,5 , The range of X is 1,2,.,491 . Because 490 parts are conforming, a n