Course Name Code Semester T+U Hours Credit ECTS
Dynamic Programming ENM 433 7 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Optional
Course Coordinator Dr.Öğr.Üyesi NEVRA AKBİLEK
Course Lecturers
Course Assistants
Course Category
Course Objective Teaching students dynamic programming techniques where possible and providing them advantages of this technique.
Course Content Network problems, Inventory problems, Resource Allocation problems, Knapsack problems, Equipment replacement problems, Wagner Within algorithm, Silver Meal heuristics, Probabilistic dynamic programming, Probabilistic stok problems,Using Excel and WinOSP in Dynamic programming problems
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Introduction Lecture, Question-Answer, Discussion, Testing, Oral Exam,
2 Network problems Lecture, Question-Answer, Drilland Practice, Testing, Homework,
3 Shortest path problems Lecture, Question-Answer, Problem Solving, Testing, Homework,
4 Inventory problems Lecture, Question-Answer, Problem Solving, Testing, Homework,
5 Resource Allocation problems Lecture, Question-Answer, Problem Solving, Testing, Homework,
6 Generalized Resource Allocation problems Lecture, Question-Answer, Problem Solving, Testing, Homework,
7 Knapsack problems Lecture, Question-Answer, Problem Solving, Testing, Homework,
8 Equipment replacement problems Lecture, Question-Answer, Problem Solving, Testing, Homework,
9 Network illustrations of special examples Lecture, Question-Answer, Problem Solving, Testing, Homework,
10 Wagner Within algorithm Lecture, Question-Answer, Problem Solving, Testing, Homework,
11 Silver Meal heuristics Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Motivations to Show, Self Study, Problem Solving, Testing, Homework, Project / Design, Performance Task,
Week Course Topics Preliminary Preparation
1 Introduction
2 Network problems
3 Shortest path problems
4 Inventory problems
5 Resource Allocation problems
6 Generalized Resource Allocation problems
7 Knapsack problems
8 Equipment replacement problems
9 Network illustrations of special examples
10 Wagner Within algorithm
11 Silver Meal heuristics
12 Probabilistic dynamic programming
13 Probabilistic stok problems
14 Using Excel and WinOSP in Dynamic programming problems
Resources
Course Notes Winston W.L. Operations Research : Applications and Algorithms , Canada, Brooks/Cole
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Engineering graduates with sufficient knowledge background on science and engineering subjects of their related area, and who are skillful in implementing theoretical and practical knowledge for modelling and solving engineering problems. X
2 Engineering graduates with skills in identifying, describing, formulating and solving complex engineering problems, and thus,deciding and implementing appropriate methods for analyzing and modelling. X
3 Engineering graduates with skills in designing a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; for this purpose, skills in implementing modern design methods. X
4 Engineering graduates with skills in developing, selecting and implementing modern techniques and tools required for engineering applications as well as with skills in using information technologies effectively. X
5 Engineering graduates with skills in designing and conducting experiments, collecting data, analyzing and interpreting the results in order to evaluate engineering problems. X
6 Engineering graduates who are able to work within a one discipline or multi-discipline team,as well as who are able to work individually X
7 Engineering graduates who are able to effectively communicate orally and officially in Turkish Language as well as who knows at least one foreign language
8 Engineering graduates with motivation to life-long learning and having known significance of continuous education beyond undergraduate studies for science and technology X
9 Engineering graduates with well-structured responsibilities in profession and ethics X
10 Engineering graduates having knowledge about practices in professional life such as project management, risk management and change management, and who are aware of innovation and sustainable development. X
11 Engineering graduates having knowledge about universal and social effects of engineering applications on health, environment and safety, as well as having awareness for juridical consequences of engineering solutions. X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 70
1. Kısa Sınav 5
2. Kısa Sınav 5
1. Ödev 20
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 10 10
Quiz 2 5 10
Assignment 1 5 5
Final examination 1 15 15
Total Workload 136
Total Workload / 25 (Hours) 5.44
dersAKTSKredisi 5