ie431 introduction to optimization theory2013

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IE431 Introduction to Optimization Theory Semester: 2013 Spring Class Hours: Tue, Thu 10:30 ~ 12:00 Classroom: Industrial Management Building (E2-2) #1122 Objective s & Outlines This class introduces various management-innovation strategies and Operations Research (O.R.) models. For example, some of the field-attractive innovation strategies including FMS, Outsourcing, Team Approach, Modular Approach, Packet Processing, M&A, and Data-Base Approach are discussed first. Then, some major OR models including Mathematical Programming, Inventory, Scheduling, Networks, Queueing, and Reliability are reviewed on their principles and applications, for which discussions are made on the important optimization techniques including Differential method, Simplex method, Gradient method, Lagrangian relaxation method, Branch-and-bound method, and Combinatorial optimization, along with several Meta- heuristic methods (Tabu, Genetics Algorithm, Fibonacci Search, Neural Networks). Instructor Information Name: Dr. Chang Sup Sung Email: [email protected] Phone: 042-350-3131 Room: Industrial Management Building (E2-2) #3107 Office hour: Tue, Thu 13:30-14:30 or by appointment Homepage http://orlab.kaist.ac.kr/multimedia/frame/index.htm Grading Class Participation & Home work(20%), Midterm(30%), Final( 50%) Text

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Page 1: IE431 Introduction to Optimization Theory2013

IE431 Introduction to Optimization TheorySemester: 2013 Spring

Class Hours: Tue, Thu 10:30 ~ 12:00

Classroom: Industrial Management Building (E2-2) #1122

Objectives &

Outlines

This class introduces various management-innovation strategies and Operations

Research (O.R.) models. For example, some of the field-attractive innovation

strategies including FMS, Outsourcing, Team Approach, Modular Approach,

Packet Processing, M&A, and Data-Base Approach are discussed first. Then, some

major OR models including Mathematical Programming, Inventory, Scheduling,

Networks, Queueing, and Reliability are reviewed on their principles and

applications, for which discussions are made on the important optimization

techniques including Differential method, Simplex method, Gradient method,

Lagrangian relaxation method, Branch-and-bound method, and Combinatorial

optimization, along with several Meta-heuristic methods (Tabu, Genetics

Algorithm, Fibonacci Search, Neural Networks).

Instructor Information

Name: Dr. Chang Sup Sung

Email: [email protected]

Phone: 042-350-3131

Room: Industrial Management Building (E2-2) #3107

Office hour: Tue, Thu 13:30-14:30 or by appointment

Homepage      http://orlab.kaist.ac.kr/multimedia/frame/index.htm

Grading          Class Participation & Home work(20%), Midterm(30%), Final( 50%)

Text

1. "Introduction to Optimization Theory" written by Chang Sup Sung only for this class.

2. "경영과학개론" (저자: 성창섭 외), 교우사, 2009 년 2 월 출판.

3. "Introduction to Operations Research" by Hillier & Lieberman, McGraw-Hill, 1997.

4. Lecture note download: class homepage

Course Schedule

 Week   Topics  Comments

Page 2: IE431 Introduction to Optimization Theory2013

1

Introduction  

2

Overview on O.R.  

3

Model Classification 1  

4

Model Classification 2  

5

Decision Making Process  

6

Classical Optimization Theory 1  

7

Classical Optimization Theory 2  

8

Midterm Exam.  

9

The Gradient Method 1  

10

The Gradient Method 2  

11

Integer Programming  

12

Ubiquitous Era  

13

Feasibility Study  

14

Preliminary Design  

15

Management Science  

16

Final Exam.  

T.A. Information: to be announced