ECTS - Decision Process and Optimization in Logistics
Decision Process and Optimization in Logistics (LOG430) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Decision Process and Optimization in Logistics | LOG430 | Area Elective | 3 | 0 | 0 | 3 | 6 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Drill and Practice. |
| Course Lecturer(s) |
|
| Course Objectives | The basic aim of this course is to recognize students a good foundation in the theory and applications of linear programming problems as well as an appreciation of its potential applications extensively in such diverse areas as logistics, manufacturing, financial planning etc. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Linear programming, formulating problems, modeling, selection of solution algorithm for models and computer assisted model solving and test, simplex algorithm, sensitivity analysis, duality analysis. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction to International Trade and Model Building | Course Book, Chapter 1 |
| 2 | The Process of Model Building | Course Book, Chapter 2 and 3 http://ocw.mit.edu/courses/sloan-school-of-management/15-093j-optimization-methods-fall-2009/lecture-notes/, lecture 1 and 2 |
| 3 | Introduction to Linear Programming | Course Book, Chapter 4 |
| 4 | Problem Analysis in Linear Programming | Course Book, Chapter 4 |
| 5 | Restrictions and Solutions Techniques | Course Book, Chapter 4 |
| 6 | Graphical Solutions and Optimization | Course Book, Chapter 5 |
| 7 | Midterm Exam | |
| 8 | Sample Company Process and Decision | Sample Profit-cost Analysis |
| 9 | The Simplex Algorithm | Course Book, Chapter 7 http://ocw.mit.edu/courses/sloan-school-of-management/15-093j-optimization-methods-fall-2009/lecture-notes/ lecture 3 and 4 |
| 10 | Network Optimization Models | Course Book, Chapter 7 |
| 11 | Sensitivity Analysis and Duality | Course Book, Chapter 8 http://ocw.mit.edu/courses/sloan-school-of-management/15-093j-optimization-methods-fall-2009/lecture-notes/ lecture 5-6 and 7 |
| 12 | Transportation, Assignment and Transshipment Problems | Course Book, Chapter 8 |
| 13 | Sensitivity and Duality Analysis in Transshipment Problems | Course Book, Chapter 9 |
| 14 | Sample analysis | |
| 15 | Comprehensive Course Overview | |
| 16 | Final Exam |
Sources
| Course Book | 1. Operations Research Models and Methods, Paul A. Jensen and Jonathan F. Bard, John Wiley and Sons, 2003. |
|---|---|
| 2. Introduction to Operations Research, Frederick S. Hillier, Gerald J. Lieberman, Ninth Edition, Mc GrawHill, 2010. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 1 | 10 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 1 | 10 |
| Presentation | - | - |
| Project | 1 | 10 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 5 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | They acquire the skills to understand, explain, and use the basic concepts and methods of economics. | |||||
| 2 | Acquires macro-economic analysis skills. | |||||
| 3 | Acquire microeconomic analysis skills. | |||||
| 4 | Understands the formulation and implementation of economic policies at local, national, regional and/or global levels. | |||||
| 5 | Learn different approaches to the economy and economic issues. | |||||
| 6 | Learn qualitative and quantitative research techniques in economic analysis. | |||||
| 7 | Improving the ability to use modern software, hardware and/or other technological tools. | |||||
| 8 | Develops intra-disciplinary and inter-disciplinary team work skills. | |||||
| 9 | Contributes to open-mindedness by encouraging critical analysis, discussion, and/or lifelong learning. | |||||
| 10 | Develops a sense of work ethics and social responsibility. | |||||
| 11 | Develops communication skills. | |||||
| 12 | Improving the ability to effectively apply knowledge and skills in at least one of the following areas: Economic policy, public policy, international economic relations, industrial relations, monetary and financial relations | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | |||
| Presentation/Seminar Prepration | |||
| Project | 1 | 30 | 30 |
| Report | |||
| Homework Assignments | 1 | 20 | 20 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 20 | 20 |
| Prepration of Final Exams/Final Jury | 1 | 30 | 30 |
| Total Workload | 148 | ||