Information Package / Course Catalogue
| Computer Engineering | |||||
| Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
Ders Genel Tanıtım Bilgileri
| School/Faculty/Institute | Faculty of Engineering | |||||
| Course Code | IE 305 | |||||
| Course Title in English | Modeling and Methods in Optimization | |||||
| Course Title in Turkish | Modelleme ve Optimizasyonda Yöntemler | |||||
| Language of Instruction | EN | |||||
| Type of Course | Select | |||||
| Level of Course | Select | |||||
| Semester | Fall | |||||
| Contact Hours per Week |
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| Estimated Student Workload | 151 hours per semester | |||||
| Number of Credits | 6 ECTS | |||||
| Grading Mode | Standard Letter Grade | |||||
| Pre-requisites |
IE 202 - Operations Research I IE 202 - Operations Research I |
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| Expected Prior Knowledge | None | |||||
| Co-requisites | None | |||||
| Registration Restrictions | None | |||||
| Overall Educational Objective | ||||||
| Course Description | ||||||
| Course Description in Turkish |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) identify network structure in optimization problems and use suitable solution methods; 2) formulate good mathematical models; 3) explore heuristic algorithms for optimization problems; 4) design suitable heuristic algorithms for optimization problems, analyze and interpret the results, and draw conclusions; 5) give a demonstration of a designed algorithm; 6) function effectively as a member of a team; |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| 1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ||||||
| 2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ||||||
| 3) An ability to communicate effectively with a range of audiences | ||||||
| 4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ||||||
| 5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ||||||
| 6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ||||||
| 7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. |
Relation to Program Outcomes and Competences
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | H | Exam |
| 2) | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | S | Exam |
| 3) | An ability to communicate effectively with a range of audiences | H | Project |
| 4) | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | N | |
| 5) | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | H | Project |
| 6) | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | H | Exam,Project |
| 7) | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies. | S | Project |
| Prepared by and Date | HANDE KÜÇÜKAYDIN , |
| Course Coordinator | HANDE KÜÇÜKAYDIN |
| Semester | Fall |
| Name of Instructor | Asst. Prof. Dr. HANDE KÜÇÜKAYDIN |
Course Contents
| Week | Subject |
| 1) | Network Optimization Models: Shortest Path Problem, Minimal Spanning Tree Problem |
| 2) | Network Optimization Models: Maximum Flow Problem |
| 3) | Building LP Models |
| 4) | Interpreting and Using LP solutions |
| 5) | Interpreting and Using LP solutions, Combinatorial Optimization Problems |
| 6) | Computational Complexity, Heuristics for Combinatorial Optimization: Introduction, Reformulation, Rounding and Decomposition |
| 7) | Heuristics for Combinatorial Optimization: List-processing Heuristics, Neighborhoods and Neighbors, Steepest Descent |
| 8) | Heuristics for Combinatorial Optimization: List-processing Heuristics, Neighborhoods and Neighbors, Steepest Descent |
| 9) | Heuristics for Combinatorial Optimization: Simulated Annealing, Tabu Search, Genetic Algorithms |
| 10) | Non-linear Models in One Variable |
| 11) | Non-linear Models: Convexity and Unconstrained Optimization |
| 12) | Non-linear Models: Constrained Optimization |
| 13) | Integer Linear Models |
| 14) | Deterministic Dynamic Programming |
| 15) | Final Examination Period |
| 16) | Final Examination Period |
| Required/Recommended Readings | Williams, H. P. (2013). Model Building in Mathematical Programming (5th Edition). Wiley Taha, H. A. (2011). Operations Research: An Introduction (9th Edition). Upper Saddle River, New Jersey: Pearson | ||||||||||||||||||
| Teaching Methods | Lectures/contact hours using “flipped classroom” as an active learning technique | ||||||||||||||||||
| Homework and Projects | 2 quizzes and 1 group project (groups of 2 students) | ||||||||||||||||||
| Laboratory Work | None | ||||||||||||||||||
| Computer Use | Visual Basic for Applications | ||||||||||||||||||
| Other Activities | None | ||||||||||||||||||
| Assessment Methods |
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| Course Administration |
hande.kucukaydin@mef.edu.tr +902123953631 Instructor’s office and phone number: 5th Floor, (0212) 3953631 office hours: Tuesday 10:00-12:00 email address: hande.kucukaydin@mef.edu.tr Rules for attendance: Minimum attendance requirement is 70%. Missing a quiz: Provided that proper documents of excuse are presented, a make-up exam will be given for each missed quiz. Missing a project: Project deadlines are always extendable up to 72 hours, with submissions late for (0,24] hours receive 70% of the credit they get, (24,48] hours receive 35% , and (48,72] receive 10%. Missing a midterm: Provided that proper documents of excuse are presented, a make-up exam will be given for each missed midterm. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations (http://3fcampus.mef.edu.tr/uploads/cms/webadmin.mef.edu.tr/4833_2.pdf ) |
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ECTS Student Workload Estimation
| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 3 | 1.5 | 77 | ||
| Project | 1 | 5 | 20 | 25 | |||
| Quiz(zes) | 2 | 4 | 0.5 | 9 | |||
| Midterm(s) | 1 | 20 | 1.5 | 21.5 | |||
| Final Examination | 1 | 25 | 2 | 27 | |||
| Total Workload | 159.5 | ||||||
| Total Workload/25 | 6.4 | ||||||
| ECTS | 6 | ||||||