ADVANCED OPERATION RESEARCH

AIM

This course aims to provide necessary information for mathematical optimization and its applications. It also aims to teach students how to use AMPL, a mathematical modeling language, for solving mathematical programming problems.

CONTENT

This course contains; Introduction to Optimization,Linear Programming,Simplex Method,Nonlinear Programming-1,Nonlinear Programming-2,Introduction to AMPL,Production Models using AMPL,Diets, Blending, and Scheduling Models using AMPL,Transportation, Assignment, and Minimum-Cost Flow Models using AMPL ,Multicommodity and multiperiod models using AMPL,Simple Sets and Indexing in AMPL,Compound Sets and Indexing in AMPL; Parameters and Expressions in AMPL ,Specifying Data in AMPL,Network Linear Programs using AMPL.

1. 1

   Students will be able to model a problem using mathematical programming

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

2. 2

   Students will be able to solve small-sized problems using mathematical programming.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

3. 3

   Students will be able to construct an AMPL model of a mathematical programming problem

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

4. 4

   Students will be able to solve a mathematical programming problem using AMPL.

   Taught by: Discussion Method, Question - Answer Technique, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

WEEKLY PLAN

1. WEEK 0

   Introduction to Optimization

2. WEEK 1

   Linear Programming

3. WEEK 2

   Simplex Method

4. WEEK 3

   Nonlinear Programming-1

5. WEEK 4

   Nonlinear Programming-2

6. WEEK 5

   Introduction to AMPL

7. WEEK 6

   Production Models using AMPL

8. WEEK 7

   Diets, Blending, and Scheduling Models using AMPL

9. WEEK 8

   Transportation, Assignment, and Minimum-Cost Flow Models using AMPL

10. WEEK 9

    Multicommodity and multiperiod models using AMPL

11. WEEK 10

    Simple Sets and Indexing in AMPL

12. WEEK 11

    Compound Sets and Indexing in AMPL; Parameters and Expressions in AMPL

13. WEEK 12

    Specifying Data in AMPL

14. WEEK 13

    Network Linear Programs using AMPL

ASSESSMENT

• Rate of Midterm Exam to Success30%
• Rate of Final Exam to Success70%

WORKLOAD

READING

• Frederik S. Hillier, Gerald J. Lieberman, Introduction to Operations Research, McGraw Hill

TEACHING STAFF

• Lect.Dr. Esin TETİKCOORDINATOR
• Assoc.Prof. Yasin GÖÇGÜN