GE288

GE330: Operations Research Methods for Profit and Value Engineering
Spring 2006

12:00-12:50pm Tues & 12:00-1:50pm Thurs

Room 103 TB
Home Page: http://www.ge.uiuc.edu/pdlab/GE330.htm

Course Catalog Description:
Credit 3 hours. Introduction to an operations-research approach to engineering decision making: economic analysis of alternatives; linear, integer, basic nonlinear, and dynamic programming with specific application to engineering problems in profit and value; decision theory.

Prerequisite(s):

CS 101, GE 161, MATH 225, and MATH 230, or consent of instructor

Instructor:

Prof. Ali Yassine
313 Transportation Building

Phone: 333-8765
Email: yassine@uiuc.edu

Office Hours: 11:00-12:00 Thurs

If the above timing does not suit you, please email me to set up an appointment.

Teaching Assistant:

Joe Bradley
304 Transportation Building

Phone: 333-7621, Email: jabradly@uiuc.edu
Office Hours: Monday 10:00-11:30am and Wednesday 1:00-2:30pm.

Course objectives:

After completing the course, the student will be able to:

List the analytical tools used to solve profit and value maximization problems
Describe the key steps in the solving various optimization problems, such as the simplex method and dynamic programming
Solve linear programs, network optimization problems, dynamic programming problems, and decision analysis problems
Derive the impact of changing the problem parameters such as resources or per-unit profit on the maximum profit or value
Formulate a business decision-making problem as an LP, dynamic program, or a decision tree
Optimize the allocation of resources to maximize profit or minimize cost in an engineering business context
Apply theorems and numerical techniques of linear algebra and probability theory
Differentiate between convex and non-convex spaces
Demonstrate necessary and sufficient conditions for optimality
Understand the concepts of duality and adjoint systems

Text:

Hamdy S. Taha, Operations Research: An Introduction, Prentice Hall, Seventh Edition.

Software:

Microsoft Excel will be used for all homework problems that require the use of software. In addition we will use the "TORA" software provided with your textbook. However, I recommend using Excel whenever possible.

Homework:

Homework problems will be assigned weekly throughout the semester. Each homework assignment is due on Tuesday of each week. However, the homework will neither be collected nor graded. It is imperative to make sure that you do the homework on timely basis in order to solve the weekly short quiz. The homework solutions will be posted on the course web each Tuesday after the class ends.

Quizzes:

A 10-15 minutes quiz will be given EVERY Thursday (for exceptions, please check the detailed course schedule on page 2). The quiz will have one or two problems taken from the assigned homework problems that are due on Tuesday of the same week. There will be nine short quizzes which will account for 20% of your final grade. I will drop the lowest TWO quiz scores and calculate your quiz total based on the highest seven quiz scores. No make-up quizzes will be given under any circumstances!

Examinations:

There will be TWO midterm exams (25% each) and a final exam (30%).
Exams are CLOSED BOOK and CLOSED NOTES, except for a single 8.5x11 inch sheet (you can use both sides) of handwritten notes for each mid-term exam and the final exam.
No make-up exams will be given unless in extreme circumstances and with prior arrangement with the instructor.
The final exam is CUMULATIVE, but new chapter material will be emphasized on the final exam.
Each student must bring a current picture ID in order to be allowed to take the exam. ANY student not having a picture ID will NOT be allowed to take the exam.
Dishonest conduct related to any examination or quiz will not be tolerated. Students who cheat will receive a failing grade (F). Cheating includes but is not limited to GIVING / RECEIVING unauthorized help and the use of unauthorized material during an examination.

Tentative Grading Scale:

Grade ≥ 88	A
77 ≤ Grade ≤ 87	B
65 ≤ Grade ≤ 76	C
50 ≤ Grade ≤ 64	D
Grade ≤ 49	F

LECTURE SCHEDULE

Date

Topic

Chap.

HW*

Homework Solution**

Notes

1-17

1-19

Introduction

Linear Programming - Graphical Solution

1, 2.1

2.2, 2.3

1-24

1-26

Linear Programming - problem session - HW #1 due

Linear Programming- Computer solution & Formulation

2.4, 2.5

Taha text

p.17: 4, 5

p.20: 5, 6

p.26: 5, 8

p.31: 1, 2

HW#1-Solution

Using Excel to solve LPs:

The Reddy Mikks Company Example

2-31

2-2

Linear Programming - problem session - HW #2 due

Simplex Method - Quiz 1

3.1→3.5

Taha text

p.45: 1, 3a

p.61: 5a, 15

Handout

HW#2-Solution

Using Excel to solve LPs : Word document , Excel File

2-7

2-9

Simplex Method - problem session - HW #3 due

Sensitivity Analysis & Duality - Quiz 2

4.1→4.3, 4.5

Taha text

p.78: 2

p.90: 3, 4

Handout

HW#3-Solution

Sensitivity analysis using Excel: Sensitivity analysis , A simple case study

2-14

2-16

Sensitivity Analysis & Duality - problem session - HW #4 due

Revised Simplex Method - Quiz 3

7.1, 7.2, 7.5

Taha text

p.119: 4 - p.125: 2

p.132: 2 - p.134: 3

p.147: 3

p.151: 5(a,b,c,d,e only)

p.157: 2 - p.158: 3

HW#4-Solution

Required Reading: Using Excel to solve LPs by the Revised Simplex Method: Excel file and Documentation

2-21

2-23

Review for Midterm I

MIDTERM I. Rm 103 & 203TB.

Chapters

1,2, 3,4

OLD Exam

- Spring 2003

Midterm1-solution

2-28

3-2

Revised Simplex Method - problem session - HW #5 due

Transportation Model

5.1→5.4

Taha Text

p.304: 2 (b,c only) & 3

p.325: 3,5

HW#5-Solution

Excel file to solve the Transportation Model: Transportation-Solver

3-7

3-9

Transportation Model - problem session - HW #6 due

Network Models - Quiz 4

6.1→6.3, 6.6

Taha Text

p.169: 2 & 6a (only)

p.176: 7 (formulate only)

p.192: 1 & 2 (a,b only)

p.201: 5

HW#6-Solution

Excel file to solve the Shortest Route problem: Shortest Route-Solver

3-14

3-16

Network Models - problem session - HW #7 due

Deterministic Dynamic Programming - Quiz 5

10.1→ 10.3

Taha Text

p.218: 3 & 4

p.228: 3

p.270: 6

p.279: 4 & 5

HW#7-Solution

3-21

3-23

Spring Recess

3-28

3-30

Deterministic Dynamic Program - problem session - HW #8 due

Deterministic Inventory Models - Quiz 6

11.1→11.3

Taha Text

p.404: 2

p.406: 2

p. 412: 5,9

HW#8-Solution

4-4

4-6

Review for Midterm II

MIDTERM II. Rm 103 & 203TB.

Chapters

5,6,7, 10

OLD Exam

- Spring 2003

Midterm2-solution

4-11

4-13

Deterministic Inventory Models - problem session - HW #9 due

Introduction to Probability - Quiz 7

12.1, → 12.3

Taha Text

p.433: 4, 7

p.439: 3, 4

p. 448: 3

p. 455: 2

HW#9-Solution

4-18

4-20

Introduction to Probability - problem session - HW #10 due

Decision Analysis (DA) - Quiz 8

14.1→14.3

Taha Text

p. 464: 1

p. 465: 2, 3

p. 466: 2, 7

p. 469: 2

+ Handout

HW#10-Solution

4-25

4-27

Decision Analysis - problem session - HW #11 due

Classical Optimization Theory - Quiz 9

Taha Text

p. 511: 2, 6

p. 516: 4, 8

p. 522: 3, 4

p. 531: 2, 3

HW#11-Solution

5-2

5-4

Review

No Class - Reading period

Extra problems on DA will be distributed in class

5-11

FINAL EXAM. Time: 7-10pm.

Rm. 100 MSEB

TBD

OLD Exam

- Spring 2003

Final-solution

You are allowed ONE page (double sided) of hand written notes

Final Grading Scale:

Grade ≥ 95	A+
Grade ≥ 90	A
80 ≤ Grade ≤ 89	B
67 ≤ Grade ≤ 79	C
50 ≤ Grade ≤ 66	D
Grade ≤ 49	F

*Click on the word "Handout" to get a MS Word file for the additional homework problems.

**The homework solutions will be posted each Tuesday after the lecture.