nstructor: Metin Türkay
Office: ENG-205
Phone: 1586
E-Mail: mturkay@ku.edu.tr
Classes: Mo, We: 09:30-10:45, ENG-B30
Office Hours: Mo, We: 11:00-12:00
Course Web Page: http://courseware.ku.edu.tr/indr363/
TAs: S. Boğ & U. Kaplan
ENG-Z08, ENG-210
1767, 2648
Brief Description
This course is designed to expose students to the concepts of optimization models and solution methods that include integer variables and nonlinear constraints. The topics covered include: introduction to modeling with integer variables and integer programming; dynamic programming; convexity and nonlinear optimization; applications of various optimization methods in manufacturing, product design, communications networks, transportation, supply chain, and financial systems.
Textbook
Hillier, F.S. and G.J. Lieberman, “Introduction to Operations Research”, 8th Ed., 2005, McGraw Hill, New York.
Problem Sessions and Computer Laboratory
In order to facilitate the topics covered, this course includes problem sessions and computer laboratory. The problem sessions are intended for strengthening basic problem solving skills and reinforcing the material covered in the lectures. The computer laboratory sessions cover basic skills in developing models and solution algorithms for solving the type of problems covered in the lectures using a software platform, OPL Studio for integer programming problems and GAMS for nonlinear programming problems.
Classroom Participation
The involvement of the student in all class activities, including computer laboratory and problem sessions, is essential and will be graded.
Homework and Computer Exercises
Homework is assigned to expose students to more complex problems and understanding of the theory, and to evaluate their abilities and knowledge. Students should be prepared to spend considerable time for preparing homework. Students are expected to submit their homework before the due date and time. In addition, there are computer exercises for modeling and solution of mathematical programming problems. The aim of the computer exercises is to help students gain some hands-on experience with state-of-the-art mathematical programming software, OPL Studio. The computer exercises must be submitted by the announced deadline. Each student is required to develop the computer exercises alone from start to end.
Exams
Exams for this course are targeted at evaluating the performance of students. So no form of information exchange during the exams will be permitted. There will always be a reasonable time limit at the exams. There are two Midterm exams during the semester and a Final exam at the end of the semester.
Final grades will be determined as follows:
Mid-Term I | 25% |
Mid-Term II | 35% |
Final Exam | 40% |
Course Outline
Date | Subject | Material |
September 26-September 28 | Special Cases of the Simplex Method The Transportation Problem The Assignment Problem | Chapter 8 Notes |
October 3-October 24 | Network Optimization Models The Shortest-Path Problem The Minimum Spanning Tree Problem The Maximum Flow Problem The Minimum Cost Flow Problem The Network Simplex Method | Chapter 9 Notes 1 Notes |
October 26 | Mid-Term I | Sample Exam |
November 14-November 23 | Integer Programming Integer Programming Models Integer Programming Models with Binary Variables The Branch-and-Bound Method for Solving Integer Programming Problems Other Methods for Solving Integer Programming Problems | Chapter 12 Notes |
November 28-December 6 | Dynamic Programming Introduction to Dynamic Programming Problems Deterministic Dynamic Programming Stochastic Dynamic Programming | Chapter 11 Notes |
December 7 | Mid-Term II | Sample Exam |
December 12-January 4 | Nonlinear Programming Introduction to Nonlinear Programming Types of Nonlinear Programming Problems Single-Variable Unconstrained Optimization Multivariable Unconstrained Optimization Constrained Optimization and the Karush-Kuhn-Tucker (KKT) Optimality Conditions Special Cases of Nonlinear Programming Problems | Chapter 13 Notes |
January 20 | Final | Sample Exam |
Note: Topics to be covered and grade percentages may be modified by the course instructor.
Academic Honesty
Honesty and trust are important to all of us as individuals. Students and faculty adhere to the following principles of academic honesty at Koç University:
Individual accountability for all individual work, written or oral: Copying from others or providing answers or information, written or oral, to others is cheating.
Providing proper acknowledgment of original author: Copying from another student’s paper or from another text without written acknowledgment is plagiarism.
Study or project group activity is effective and authorized teamwork: Unauthorized help from another person or having someone else write one’s paper or assignment is collusion.
Cheating, plagiarism, and collusion are serious offenses resulting in an F grade and disciplinary action.
Attendance Policy
All students are required to attend classes and discussion sessions such as tutorials, labs and problem sessions. The course instructor will take attendance. The students who fail to attend 1/3 of classes and discussion sessions may get an automatic F.
Date | Date Due | Assignment | Solutions |
Oct. 5, 2005 | Oct. 12. 2005 | 9.3-1, 9.3-3, 9.3-4, 9.3-6, 9.4-2, 9.4-3 Dijkstra’s algorithm can be used for solving the shortest path problems. | Solutions |
Oct. 17, 2005 | Oct. 24. 2005 | 9.5-1, 9.5-3, 9.5-5, 9.6-2, 9.6-4, 9.7-1, 9.7-3 | Solutions |
Nov. 30, 2005 | Dec. 7, 2005 | 11.1-2, 11.1-6, 11.3-1, 11.3-4, 11.4-6, 11.5-1, 11.6-1 | Solutions |
Dec. 29, 2005 | Jan. 7, 2006 | 10.2-2, 10.3-1, 10.3-6, 10.3-8, 10.3-17, 10.4-2 | |
Jan. 4, 2006 | Jan. 16, 2006 | 12.1-3, 12.2-5, 12.2-7, 12.3-4, 12.4-1,12.4-6, 12.5-6, 12.6-5,12.7-4 |
Date | Announcement |
Oct. 24, 2005 | Mid Term I of Fall 2004 |
Date | Grade posted |
November 20, 2005 | MT1 |
December 26, 2005 | MT1&MT2 |
February 05, 2006 | MT1&MT2&Final&Total |