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Course Description Course Name : Operations Research Course Code : İSB404 Course Type : Optional Level of Course : First Cycle Year of Study : 4 Course Semester : Spring (16 Weeks) ECTS : 5 Name of Lecturer(s) : Prof.Dr. SELAHATTİN KAÇIRANLAR Learning Outcomes of the Course : Understand the concept of the model and improve the model solve balanced and unbalanced transportation problems solve the assignment models solve Network models and the problems of the shortest path understand maximum flow model understand capacity of the minimum cost flow problem understand goal programming algorithms apply Integer programming algorithms do decision analysis solve game theory problems Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : To teach basic ideas of operations research techniques Course Contents : Operations research Techniques, Art of modelling, Transportation model, The assignment model, Network models, Shortest Route Problem, Goal Programming, Integer linear programming, Decision analysis and game theory Language of Instruction : Turkish Work Place : Faculty of Arts and Sciences Annex Classrooms   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 The concept of model, model development Source reading Lecture, discussion and problem-solving,using package 2 Transportation Models Source reading Lecture, discussion and problem-solving,using package 3 Unbalanced transportation problems Source reading Lecture, discussion and problem-solving,using package 4 Assignment Model Source reading Lecture, discussion and problem-solving,using package 5 Network Models, the shortest path problem Source reading Lecture, discussion and problem-solving,using package 6 Maximum Flow Model Source reading Lecture, discussion and problem-solving,using package 7 Capacity of the minimum cost flow problem Source reading Lecture, discussion and problem-solving,using package 8 mid-term exam Rewview the topics discussed in the lecture notes and sources written exam 9 Goal Programming Source reading Lecture, discussion and problem-solving,using package 10 Goal programming algorithms Source reading Lecture, discussion and problem-solving,using package 11 Integer programming Source reading Lecture, discussion and problem-solving,using package 12 Integer programming algorithms Source reading Lecture, discussion and problem-solving,using package 13 Decision Analysis Source reading Lecture, discussion and problem-solving 14 Game theory Source reading Lecture, discussion and problem-solving 15 Game theory Source reading Lecture, discussion and problem-solving 16/17 Final exam Rewview the topics discussed in the lecture notes and sources written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Yöneylem Araştırması, Ahmet Öztürk, Ekin Yayınevi,2009 Required Course Material(s)  Yöneylem Araştırması, Hamdy A. Taha(Çevirenler : Ş. Alp Baray- Şakir Esnaf), Literatür Yayıncılık, 2000  Ayanoğlu, M.(2006)Yönetim Bilimi (Yöneylem araştırması ders notları)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 80     Homeworks/Projects/Others 5 20 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Utilize computer systems and softwares 4 2 Apply the statistical analyze methods 1 3 Make statistical inference(estimation, hypothesis tests etc.) 1 4 Generate solutions for the problems in other disciplines by using statistical techniques 5 5 Discover the visual, database and web programming techniques and posses the ability of writing programme 2 6 Construct a model and analyze it by using statistical packages 4 7 Distinguish the difference between the statistical methods 2 8 Be aware of the interaction between the disciplines related to statistics 4 9 Make oral and visual presentation for the results of statistical methods 4 10 Have capability on effective and productive work in a group and individually 4 11 Develop scientific and ethical values in the fields of statistics-and scientific data collection 1 12 Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 5 13 Emphasize the importance of Statistics in life 4 14 Define basic principles and concepts in the field of Law and Economics 0 15 Produce numeric and statistical solutions in order to overcome the problems 5 16 Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 5 17 Use proper methods and techniques to gather and/or to arrange the data 1 18 Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs 0 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 3 42 Assesment Related Works     Homeworks, Projects, Others 5 3 15     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 15 15 Total Workload: 124 Total Workload / 25 (h): 4.96 ECTS Credit: 5